Development and Testing of a Two-UAV Communication Relay System

PubMed Central

Li, Boyang; Jiang, Yifan; Sun, Jingxuan; Cai, Lingfeng; Wen, Chih-Yung

2016-01-01

In the development of beyond-line-of-sight (BLOS) Unmanned Aerial Vehicle (UAV) systems, communication between the UAVs and the ground control station (GCS) is of critical importance. The commonly used economical wireless modules are restricted by the short communication range and are easily blocked by obstacles. The use of a communication relay system provides a practical way to solve these problems, improving the performance of UAV communication in BLOS and cross-obstacle operations. In this study, a communication relay system, in which a quadrotor was used to relay radio communication for another quadrotor was developed and tested. First, the UAVs used as the airborne platform were constructed, and the hardware for the communication relay system was selected and built up. Second, a set of software programs and protocol for autonomous mission control, communication relay control, and ground control were developed. Finally, the system was fully integrated into the airborne platform and tested both indoor and in-flight. The Received Signal Strength Indication (RSSI) and noise value in two typical application scenarios were recorded. The test results demonstrated the ability of this system to extend the communication range and build communication over obstacles. This system also shows the feasibility to coordinate multiple UAVs’ communication with the same relay structure. PMID:27754369

Integrated optimization of unmanned aerial vehicle task allocation and path planning under steady wind.

PubMed

Luo, He; Liang, Zhengzheng; Zhu, Moning; Hu, Xiaoxuan; Wang, Guoqiang

2018-01-01

Wind has a significant effect on the control of fixed-wing unmanned aerial vehicles (UAVs), resulting in changes in their ground speed and direction, which has an important influence on the results of integrated optimization of UAV task allocation and path planning. The objective of this integrated optimization problem changes from minimizing flight distance to minimizing flight time. In this study, the Euclidean distance between any two targets is expanded to the Dubins path length, considering the minimum turning radius of fixed-wing UAVs. According to the vector relationship between wind speed, UAV airspeed, and UAV ground speed, a method is proposed to calculate the flight time of UAV between targets. On this basis, a variable-speed Dubins path vehicle routing problem (VS-DP-VRP) model is established with the purpose of minimizing the time required for UAVs to visit all the targets and return to the starting point. By designing a crossover operator and mutation operator, the genetic algorithm is used to solve the model, the results of which show that an effective UAV task allocation and path planning solution under steady wind can be provided.

Integrated optimization of unmanned aerial vehicle task allocation and path planning under steady wind

PubMed Central

Liang, Zhengzheng; Zhu, Moning; Hu, Xiaoxuan; Wang, Guoqiang

2018-01-01

Wind has a significant effect on the control of fixed-wing unmanned aerial vehicles (UAVs), resulting in changes in their ground speed and direction, which has an important influence on the results of integrated optimization of UAV task allocation and path planning. The objective of this integrated optimization problem changes from minimizing flight distance to minimizing flight time. In this study, the Euclidean distance between any two targets is expanded to the Dubins path length, considering the minimum turning radius of fixed-wing UAVs. According to the vector relationship between wind speed, UAV airspeed, and UAV ground speed, a method is proposed to calculate the flight time of UAV between targets. On this basis, a variable-speed Dubins path vehicle routing problem (VS-DP-VRP) model is established with the purpose of minimizing the time required for UAVs to visit all the targets and return to the starting point. By designing a crossover operator and mutation operator, the genetic algorithm is used to solve the model, the results of which show that an effective UAV task allocation and path planning solution under steady wind can be provided. PMID:29561888

Agile Information Exchange in Autonomous Air Systems

DTIC Science & Technology

2013-06-01

proportional to the information the pilot has on the target. Figure 5: Modified Procerus Unicorn UAV D. Equipment The UAV used in this experiment is...a modified Procerus Unicorn (Figure 5). Unicorns are electrically powered, Styrofoam flying wings with a 72” wingspan. Stock Unicorns are...controlled by a Kestrel autopilot, which communicates to a ground-station over a 900MHz radio link. Through the ground-station, the Unicorn operator can

Accuracy of Orthomosaic Generated by Different Methods in Example of UAV Platform MUST Q

NASA Astrophysics Data System (ADS)

Liba, N.; Berg-Jürgens, J.

2015-11-01

Development of photogrammetry has reached a new level due to the use of unmanned aerial vehicles (UAV). In Estonia, the main areas of use of UAVs are monitoring overhead power lines for energy companies and fields in agriculture, and estimating the use of stockpile in mining. The project was carried out by the order of the City of Tartu for future road construction. In this research, automation of UAV platform MUST Q aerial image processing and reduction of time spent on the use of ground control points (GCP) is studied. For that two projects were created with software Pix4D. First one was processed automatically without GCP. Second one did use GCP, but all the processing was done automatically. As the result of the project, two orthomosaics with the pixel size of 5 cm were composed. Projects allowed ensuring accuracy limit of three times of the pixel size. The project that turned out to be the most accurate was the one using ground control points to do the levelling, which remained within the error limit allowed and the accuracy of the orthomosaic was 0.132 m. The project that didn't use ground control points had the accuracy of 1.417 m.

Determination of Shift/Bias in Digital Aerial Triangulation of UAV Imagery Sequences

NASA Astrophysics Data System (ADS)

Wierzbicki, Damian

2017-12-01

Currently UAV Photogrammetry is characterized a largely automated and efficient data processing. Depicting from the low altitude more often gains on the meaning in the uses of applications as: cities mapping, corridor mapping, road and pipeline inspections or mapping of large areas e.g. forests. Additionally, high-resolution video image (HD and bigger) is more often use for depicting from the low altitude from one side it lets deliver a lot of details and characteristics of ground surfaces features, and from the other side is presenting new challenges in the data processing. Therefore, determination of elements of external orientation plays a substantial role the detail of Digital Terrain Models and artefact-free ortophoto generation. Parallel a research on the quality of acquired images from UAV and above the quality of products e.g. orthophotos are conducted. Despite so fast development UAV photogrammetry still exists the necessity of accomplishment Automatic Aerial Triangulation (AAT) on the basis of the observations GPS/INS and via ground control points. During low altitude photogrammetric flight, the approximate elements of external orientation registered by UAV are burdened with the influence of some shift/bias errors. In this article, methods of determination shift/bias error are presented. In the process of the digital aerial triangulation two solutions are applied. In the first method shift/bias error was determined together with the drift/bias error, elements of external orientation and coordinates of ground control points. In the second method shift/bias error was determined together with the elements of external orientation, coordinates of ground control points and drift/bias error equals 0. When two methods were compared the difference for shift/bias error is more than ±0.01 m for all terrain coordinates XYZ.

UAV-guided navigation for ground robot tele-operation in a military reconnaissance environment.

PubMed

Chen, Jessie Y C

2010-08-01

A military reconnaissance environment was simulated to examine the performance of ground robotics operators who were instructed to utilise streaming video from an unmanned aerial vehicle (UAV) to navigate his/her ground robot to the locations of the targets. The effects of participants' spatial ability on their performance and workload were also investigated. Results showed that participants' overall performance (speed and accuracy) was better when she/he had access to images from larger UAVs with fixed orientations, compared with other UAV conditions (baseline- no UAV, micro air vehicle and UAV with orbiting views). Participants experienced the highest workload when the UAV was orbiting. Those individuals with higher spatial ability performed significantly better and reported less workload than those with lower spatial ability. The results of the current study will further understanding of ground robot operators' target search performance based on streaming video from UAVs. The results will also facilitate the implementation of ground/air robots in military environments and will be useful to the future military system design and training community.

UAV Inspection of Electrical Transmission Infrastructure with Path Conformance Autonomy and Lidar-Based Geofences NASA Report on UTM Reference Mission Flights at Southern Company Flights November 2016

NASA Technical Reports Server (NTRS)

Moore, Andrew J.; Schubert, Matthew; Rymer, Nicholas; Balachandran, Swee; Consiglio, Maria; Munoz, Cesar; Smith, Joshua; Lewis, Dexter; Schneider, Paul

2017-01-01

Flights at low altitudes in close proximity to electrical transmission infrastructure present serious navigational challenges: GPS and radio communication quality is variable and yet tight position control is needed to measure defects while avoiding collisions with ground structures. To advance unmanned aerial vehicle (UAV) navigation technology while accomplishing a task with economic and societal benefit, a high voltage electrical infrastructure inspection reference mission was designed. An integrated air-ground platform was developed for this mission and tested in two days of experimental flights to determine whether navigational augmentation was needed to successfully conduct a controlled inspection experiment. The airborne component of the platform was a multirotor UAV built from commercial off-the-shelf hardware and software, and the ground component was a commercial laptop running open source software. A compact ultraviolet sensor mounted on the UAV can locate 'hot spots' (potential failure points in the electric grid), so long as the UAV flight path adequately samples the airspace near the power grid structures. To improve navigation, the platform was supplemented with two navigation technologies: lidar-to-polyhedron preflight processing for obstacle demarcation and inspection distance planning, and trajectory management software to enforce inspection standoff distance. Both navigation technologies were essential to obtaining useful results from the hot spot sensor in this obstacle-rich, low-altitude airspace. Because the electrical grid extends into crowded airspaces, the UAV position was tracked with NASA unmanned aerial system traffic management (UTM) technology. The following results were obtained: (1) Inspection of high-voltage electrical transmission infrastructure to locate 'hot spots' of ultraviolet emission requires navigation methods that are not broadly available and are not needed at higher altitude flights above ground structures. (2) The sensing capability of a novel airborne UV detector was verified with a standard ground-based instrument. Flights with this sensor showed that UAV measurement operations and recording methods are viable. With improved sensor range, UAVs equipped with compact UV sensors could serve as the detection elements in a self-diagnosing power grid. (3) Simplification of rich lidar maps to polyhedral obstacle maps reduces data volume by orders of magnitude, so that computation with the resultant maps in real time is possible. This enables real-time obstacle avoidance autonomy. Stable navigation may be feasible in the GPS-deprived environment near transmission lines by a UAV that senses ground structures and compares them to these simplified maps. (4) A new, formally verified path conformance software system that runs onboard a UAV was demonstrated in flight for the first time. It successfully maneuvered the aircraft after a sudden lateral perturbation that models a gust of wind, and processed lidar-derived polyhedral obstacle maps in real time. (5) Tracking of the UAV in the national airspace using the NASA UTM technology was a key safety component of this reference mission, since the flights were conducted beneath the landing approach to a heavily used runway. Comparison to autopilot tracking showed that UTM tracking accurately records the UAV position throughout the flight path.

a Light-Weight Laser Scanner for Uav Applications

NASA Astrophysics Data System (ADS)

Tommaselli, A. M. G.; Torres, F. M.

2016-06-01

Unmanned Aerial Vehicles (UAV) have been recognized as a tool for geospatial data acquisition due to their flexibility and favourable cost benefit ratio. The practical use of laser scanning devices on-board UAVs is also developing with new experimental and commercial systems. This paper describes a light-weight laser scanning system composed of an IbeoLux scanner, an Inertial Navigation System Span-IGM-S1, from Novatel, a Raspberry PI portable computer, which records data from both systems and an octopter UAV. The performance of this light-weight system was assessed both for accuracy and with respect to point density, using Ground Control Points (GCP) as reference. Two flights were performed with the UAV octopter carrying the equipment. In the first trial, the flight height was 100 m with six strips over a parking area. The second trial was carried out over an urban park with some buildings and artificial targets serving as reference Ground Control Points. In this experiment a flight height of 70 m was chosen to improve target response. Accuracy was assessed based on control points the coordinates of which were measured in the field. Results showed that vertical accuracy with this prototype is around 30 cm, which is acceptable for forest applications but this accuracy can be improved using further refinements in direct georeferencing and in the system calibration.

A Natural Interaction Interface for UAVs Using Intuitive Gesture Recognition

NASA Technical Reports Server (NTRS)

Chandarana, Meghan; Trujillo, Anna; Shimada, Kenji; Allen, Danette

2016-01-01

The popularity of unmanned aerial vehicles (UAVs) is increasing as technological advancements boost their favorability for a broad range of applications. One application is science data collection. In fields like Earth and atmospheric science, researchers are seeking to use UAVs to augment their current portfolio of platforms and increase their accessibility to geographic areas of interest. By increasing the number of data collection platforms UAVs will significantly improve system robustness and allow for more sophisticated studies. Scientists would like be able to deploy an available fleet of UAVs to fly a desired flight path and collect sensor data without needing to understand the complex low-level controls required to describe and coordinate such a mission. A natural interaction interface for a Ground Control System (GCS) using gesture recognition is developed to allow non-expert users (e.g., scientists) to define a complex flight path for a UAV using intuitive hand gesture inputs from the constructed gesture library. The GCS calculates the combined trajectory on-line, verifies the trajectory with the user, and sends it to the UAV controller to be flown.

Unmanned air vehicle: autonomous takeoff and landing

NASA Astrophysics Data System (ADS)

Lim, K. L.; Gitano-Briggs, Horizon Walker

2010-03-01

UAVs are increasing in popularity and sophistication due to the demonstrated performance which cannot be attained by manned aircraft1. These developments have been made possible by development of sensors, instrumentation, telemetry and controls during the last few decades. UAVs are now common in areas such as aerial observation and as communication relays3. Most UAVs, however, are still flown by a human pilot via remote control from a ground station. Even the existing autonomous UAVs often require a human pilot to handle the most difficult tasks of take off and landing2 (TOL). This is mainly because the navigation of the airplane requires observation, constant situational assessment and hours of experience from the pilot himself4. Therefore, an autonomous takeoff and landing system (TLS) for UAVs using a few practical design rules with various sensors, instrumentation, etc has been developed. This paper details the design and modeling of the UAV TLS. The model indicates that the UAV's TLS shows promising stability.

Unmanned air vehicle: autonomous takeoff and landing

NASA Astrophysics Data System (ADS)

Lim, K. L.; Gitano-Briggs, Horizon Walker

2009-12-01

UAVs are increasing in popularity and sophistication due to the demonstrated performance which cannot be attained by manned aircraft1. These developments have been made possible by development of sensors, instrumentation, telemetry and controls during the last few decades. UAVs are now common in areas such as aerial observation and as communication relays3. Most UAVs, however, are still flown by a human pilot via remote control from a ground station. Even the existing autonomous UAVs often require a human pilot to handle the most difficult tasks of take off and landing2 (TOL). This is mainly because the navigation of the airplane requires observation, constant situational assessment and hours of experience from the pilot himself4. Therefore, an autonomous takeoff and landing system (TLS) for UAVs using a few practical design rules with various sensors, instrumentation, etc has been developed. This paper details the design and modeling of the UAV TLS. The model indicates that the UAV's TLS shows promising stability.

Synthesis of the unmanned aerial vehicle remote control augmentation system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tomczyk, Andrzej, E-mail: A.Tomczyk@prz.edu.pl

Medium size Unmanned Aerial Vehicle (UAV) usually flies as an autonomous aircraft including automatic take-off and landing phases. However in the case of the on-board control system failure, the remote steering is using as an emergency procedure. In this reason, remote manual control of unmanned aerial vehicle is used more often during take-of and landing phases. Depends on UAV take-off mass and speed (total energy) the potential crash can be very danger for airplane and environment. So, handling qualities of UAV is important from pilot-operator point of view. In many cases the dynamic properties of remote controlling UAV are notmore » suitable for obtaining the desired properties of the handling qualities. In this case the control augmentation system (CAS) should be applied. Because the potential failure of the on-board control system, the better solution is that the CAS algorithms are placed on the ground station computers. The method of UAV handling qualities shaping in the case of basic control system failure is presented in this paper. The main idea of this method is that UAV reaction on the operator steering signals should be similar - almost the same - as reaction of the 'ideal' remote control aircraft. The model following method was used for controller parameters calculations. The numerical example concerns the medium size MP-02A UAV applied as an aerial observer system.« less

An Intuitive Graphical User Interface for Small UAS

DTIC Science & Technology

2013-05-01

reduced from two to one . The stock displays, including video with text overlay on one and FalconView on the other, are replaced with a single, graphics...INTRODUCTION Tactical UAVs such as the Raven, Puma and Wasp are often used by dismounted warfighters on missions that require a high degree of mobility by...the operators on the ground. The current ground control stations (GCS) for the Wasp, Raven and Puma tactical UAVs require two people and two user

Photovoltaic electric power applied to Unmanned Aerial Vehicles (UAV)

NASA Technical Reports Server (NTRS)

Geis, Jack; Arnold, Jack H.

1994-01-01

Photovoltaic electric-powered flight is receiving a great deal of attention in the context of the United States' Unmanned Aerial Vehicle (UAV) program. This paper addresses some of the enabling technical areas and their potential solutions. Of particular interest are the long-duration, high-altitude class of UAV's whose mission it is to achieve altitudes between 60,000 and 100,000 feet, and to remain at those altitudes for prolonged periods performing various mapping and surveillance activities. Addressed herein are studies which reveal the need for extremely light-weight and efficient solar cells, high-efficiency electric motor-driven propeller modules, and power management and distribution control elements. Since the potential payloads vary dramatically in their power consumption and duty cycles, a typical load profile has been selected to provide commonality for the propulsion power comparisons. Since missions vary widely with respect to ground coverage requirements, from repeated orbiting over a localized target to long-distance routes over irregular terrain, we have also averaged the power requirements for on-board guidance and control power, as well as ground control and communication link utilization. In the context of the national technology reinvestment program, wherever possible we modeled components and materials which have been qualified for space and defense applications, yet are compatible with civilian UAV activities. These include, but are not limited to, solar cell developments, electric storage technology for diurnal operation, local and ground communications, power management and distribution, and control servo design. And finally, the results of tests conducted by Wright Laboratory on ultralight, highly efficient MOCVD GaAs solar cells purchased from EPI Materials Ltd. (EML) of the UK are presented. These cells were also used for modeling the flight characteristics of UAV aircraft.

Photovoltaic electric power applied to Unmanned Aerial Vehicles (UAV)

NASA Astrophysics Data System (ADS)

Geis, Jack; Arnold, Jack H.

1994-09-01

Photovoltaic electric-powered flight is receiving a great deal of attention in the context of the United States' Unmanned Aerial Vehicle (UAV) program. This paper addresses some of the enabling technical areas and their potential solutions. Of particular interest are the long-duration, high-altitude class of UAV's whose mission it is to achieve altitudes between 60,000 and 100,000 feet, and to remain at those altitudes for prolonged periods performing various mapping and surveillance activities. Addressed herein are studies which reveal the need for extremely light-weight and efficient solar cells, high-efficiency electric motor-driven propeller modules, and power management and distribution control elements. Since the potential payloads vary dramatically in their power consumption and duty cycles, a typical load profile has been selected to provide commonality for the propulsion power comparisons. Since missions vary widely with respect to ground coverage requirements, from repeated orbiting over a localized target to long-distance routes over irregular terrain, we have also averaged the power requirements for on-board guidance and control power, as well as ground control and communication link utilization. In the context of the national technology reinvestment program, wherever possible we modeled components and materials which have been qualified for space and defense applications, yet are compatible with civilian UAV activities. These include, but are not limited to, solar cell developments, electric storage technology for diurnal operation, local and ground communications, power management and distribution, and control servo design. And finally, the results of tests conducted by Wright Laboratory on ultralight, highly efficient MOCVD GaAs solar cells purchased from EPI Materials Ltd. (EML) of the UK are presented. These cells were also used for modeling the flight characteristics of UAV aircraft.

Development of Open source-based automatic shooting and processing UAV imagery for Orthoimage Using Smart Camera UAV

NASA Astrophysics Data System (ADS)

Park, J. W.; Jeong, H. H.; Kim, J. S.; Choi, C. U.

2016-06-01

Recently, aerial photography with unmanned aerial vehicle (UAV) system uses UAV and remote controls through connections of ground control system using bandwidth of about 430 MHz radio Frequency (RF) modem. However, as mentioned earlier, existing method of using RF modem has limitations in long distance communication. The Smart Camera equipments's LTE (long-term evolution), Bluetooth, and Wi-Fi to implement UAV that uses developed UAV communication module system carried out the close aerial photogrammetry with the automatic shooting. Automatic shooting system is an image capturing device for the drones in the area's that needs image capturing and software for loading a smart camera and managing it. This system is composed of automatic shooting using the sensor of smart camera and shooting catalog management which manages filmed images and information. Processing UAV imagery module used Open Drone Map. This study examined the feasibility of using the Smart Camera as the payload for a photogrammetric UAV system. The open soure tools used for generating Android, OpenCV (Open Computer Vision), RTKLIB, Open Drone Map.

Ground control station software design for micro aerial vehicles

NASA Astrophysics Data System (ADS)

Walendziuk, Wojciech; Oldziej, Daniel; Binczyk, Dawid Przemyslaw; Slowik, Maciej

2017-08-01

This article describes the process of designing the equipment part and the software of a ground control station used for configuring and operating micro unmanned aerial vehicles (UAV). All the works were conducted on a quadrocopter model being a commonly accessible commercial construction. This article contains a characteristics of the research object, the basics of operating the micro aerial vehicles (MAV) and presents components of the ground control station model. It also describes the communication standards for the purpose of building a model of the station. Further part of the work concerns the software of the product - the GIMSO application (Generally Interactive Station for Mobile Objects), which enables the user to manage the actions and communication and control processes from the UAV. The process of creating the software and the field tests of a station model are also presented in the article.

A Mobile System for Measuring Water Surface Velocities Using Unmanned Aerial Vehicle and Large-Scale Particle Image Velocimetry

NASA Astrophysics Data System (ADS)

Chen, Y. L.

2015-12-01

Measurement technologies for velocity of river flow are divided into intrusive and nonintrusive methods. Intrusive method requires infield operations. The measuring process of intrusive methods are time consuming, and likely to cause damages of operator and instrument. Nonintrusive methods require fewer operators and can reduce instrument damages from directly attaching to the flow. Nonintrusive measurements may use radar or image velocimetry to measure the velocities at the surface of water flow. The image velocimetry, such as large scale particle image velocimetry (LSPIV) accesses not only the point velocity but the flow velocities in an area simultaneously. Flow properties of an area hold the promise of providing spatially information of flow fields. This study attempts to construct a mobile system UAV-LSPIV by using an unmanned aerial vehicle (UAV) with LSPIV to measure flows in fields. The mobile system consists of a six-rotor UAV helicopter, a Sony nex5T camera, a gimbal, an image transfer device, a ground station and a remote control device. The activate gimbal helps maintain the camera lens orthogonal to the water surface and reduce the extent of images being distorted. The image transfer device can monitor the captured image instantly. The operator controls the UAV by remote control device through ground station and can achieve the flying data such as flying height and GPS coordinate of UAV. The mobile system was then applied to field experiments. The deviation of velocities measured by UAV-LSPIV of field experiments and handhold Acoustic Doppler Velocimeter (ADV) is under 8%. The results of the field experiments suggests that the application of UAV-LSPIV can be effectively applied to surface flow studies.

Mission Specification and Control for Unmanned Aerial and Ground Vehicles for Indoor Target Discovery and Tracking

DTIC Science & Technology

2010-01-01

open garage leading to the building interior. The UAV is positioned north of a potential ingress to the building. As the mission begins, the UAV...camera, the difficulty in detecting and navigating around obstacles using this non- stereo camera necessitated a precomputed map of all obstacles and

UAV Trajectory Modeling Using Neural Networks

NASA Technical Reports Server (NTRS)

Xue, Min

2017-01-01

Large amount of small Unmanned Aerial Vehicles (sUAVs) are projected to operate in the near future. Potential sUAV applications include, but not limited to, search and rescue, inspection and surveillance, aerial photography and video, precision agriculture, and parcel delivery. sUAVs are expected to operate in the uncontrolled Class G airspace, which is at or below 500 feet above ground level (AGL), where many static and dynamic constraints exist, such as ground properties and terrains, restricted areas, various winds, manned helicopters, and conflict avoidance among sUAVs. How to enable safe, efficient, and massive sUAV operations at the low altitude airspace remains a great challenge. NASA's Unmanned aircraft system Traffic Management (UTM) research initiative works on establishing infrastructure and developing policies, requirement, and rules to enable safe and efficient sUAVs' operations. To achieve this goal, it is important to gain insights of future UTM traffic operations through simulations, where the accurate trajectory model plays an extremely important role. On the other hand, like what happens in current aviation development, trajectory modeling should also serve as the foundation for any advanced concepts and tools in UTM. Accurate models of sUAV dynamics and control systems are very important considering the requirement of the meter level precision in UTM operations. The vehicle dynamics are relatively easy to derive and model, however, vehicle control systems remain unknown as they are usually kept by manufactures as a part of intellectual properties. That brings challenges to trajectory modeling for sUAVs. How to model the vehicle's trajectories with unknown control system? This work proposes to use a neural network to model a vehicle's trajectory. The neural network is first trained to learn the vehicle's responses at numerous conditions. Once being fully trained, given current vehicle states, winds, and desired future trajectory, the neural network should be able to predict the vehicle's future states at next time step. A complete 4-D trajectory are then generated step by step using the trained neural network. Experiments in this work show that the neural network can approximate the sUAV's model and predict the trajectory accurately.

Ground Control Point - Wireless System Network for UAV-based environmental monitoring applications

NASA Astrophysics Data System (ADS)

Mejia-Aguilar, Abraham

2016-04-01

In recent years, Unmanned Aerial Vehicles (UAV) have seen widespread civil applications including usage for survey and monitoring services in areas such as agriculture, construction and civil engineering, private surveillance and reconnaissance services and cultural heritage management. Most aerial monitoring services require the integration of information acquired during the flight (such as imagery) with ground-based information (such as GPS information or others) for improved ground truth validation. For example, to obtain an accurate 3D and Digital Elevation Model based on aerial imagery, it is necessary to include ground-based information of coordinate points, which are normally acquired with surveying methods based on Global Position Systems (GPS). However, GPS surveys are very time consuming and especially for longer time series of monitoring data repeated GPS surveys are necessary. In order to improve speed of data collection and integration, this work presents an autonomous system based on Waspmote technologies build on single nodes interlinked in a Wireless Sensor Network (WSN) star-topology for ground based information collection and later integration with surveying data obtained by UAV. Nodes are designed to be visible from the air, to resist extreme weather conditions with low-power consumption. Besides, nodes are equipped with GPS as well as Inertial Measurement Unit (IMU), accelerometer, temperature and soil moisture sensors and thus provide significant advantages in a broad range of applications for environmental monitoring. For our purpose, the WSN transmits the environmental data with 3G/GPRS to a database on a regular time basis. This project provides a detailed case study and implementation of a Ground Control Point System Network for UAV-based vegetation monitoring of dry mountain grassland in the Matsch valley, Italy.

Guidance and Control of an Autonomous Soaring Vehicle with Flight Test Results

NASA Technical Reports Server (NTRS)

Allen, Michael J.

2007-01-01

A guidance and control method was developed to detect and exploit thermals for energy gain. Latency in energy rate estimation degraded performance. The concept of a UAV harvesting energy from the atmosphere has been shown to be feasible with existing technology. Many UAVs have similar mission constraints to birds and sailplanes. a) Surveillance; b) Point to point flight with minimal energy; and c) Increased ground speed.

An Ecological Approach to the Design of UAV Ground Control Station (GCS) Status Displays

NASA Technical Reports Server (NTRS)

Dowell, Susan; Morphew, Ephimia; Shively, Jay

2003-01-01

Use of UAVs in military and commercial applications will continue to increase. However, there has been limited research devoted to UAV GCS design. The current study employed an ecological approach to interfac e design. Ecological Interface Design (EID) can be characterized as r epresenting the properties of a system, such that an operator is enco uraged to use skill-based behavior when problem solving. When more ef fortful cognitive processes become necessary due to unfamiliar situations, the application of EID philosophy supports the application of kn owledge-based behavior. With advances toward multiple UAV command and control, operators need GCS interfaces designed to support understan ding of complex systems. We hypothesized that use of EID principles f or the display of UAV status information would result in better opera tor performance and situational awareness, while decreasing workload. Pilots flew a series of missions with three UAV GCS displays of statu s information (Alphanumeric, Ecological, and Hybrid display format). Measures of task performance, Situational Awareness, and workload dem onstrated the benefits of using an ecological approach to designing U AV GCS displays. The application of ecological principles to the design of UAV GCSs is a promising area for improving UAV operations.

Use of a Light Uav and Photogrammetric Techniques to Study the Evolution of a Landslide in JAÉN (southern Spain)

NASA Astrophysics Data System (ADS)

Fernández, T.; Pérez, J. L.; Cardenal, F. J.; López, A.; Gómez, J. M.; Colomo, C.; Delgado, J.; Sánchez, M.

2015-08-01

This paper presents a methodology for slope instability monitoring using photogrammetric techniques with very high resolution images from an unmanned aerial vehicle (UAV). An unstable area located in La Guardia (Jaen, Southern Spain), where an active mud flow has been identified, was surveyed between 2012 and 2014 by means of four UAV flights. These surveys were also compared with those data from a previous conventional aerial photogrammetric and LiDAR survey. The UAV was an octocopter equipped with GPS, inertial units and a mirrorless interchangeable-lens camera. The flight height was 90 m, which allowed covering an area of about 250 x 100 m with a ground pixel size of 2.5 cm. The orientation of the UAV flights were carried out by means of ground control points measured with GPS, but the previous aerial photogrammetric/LiDAR flight was oriented by means of direct georeferencing with in flight positioning and inertial data, although some common ground control points were used to adjust all flights in the same reference system. The DSMs of all surveys were obtained by automatic image correlation and then the differential models were calculated, allowing estimate changes in the surface. At the same time, orthophotos were obtained so horizontal and vertical displacements between relevant points were registered. Significant displacements were observed between some campaigns (some centimeters on the vertical and meters on the horizontal). Finally, we have analyzed the relation of displacements to rainfalls in recent years in the area, finding a significant temporal correlation between the two variables.

Uav Photogrammetry: Block Triangulation Comparisons

NASA Astrophysics Data System (ADS)

Gini, R.; Pagliari, D.; Passoni, D.; Pinto, L.; Sona, G.; Dosso, P.

2013-08-01

UAVs systems represent a flexible technology able to collect a big amount of high resolution information, both for metric and interpretation uses. In the frame of experimental tests carried out at Dept. ICA of Politecnico di Milano to validate vector-sensor systems and to assess metric accuracies of images acquired by UAVs, a block of photos taken by a fixed wing system is triangulated with several software. The test field is a rural area included in an Italian Park ("Parco Adda Nord"), useful to study flight and imagery performances on buildings, roads, cultivated and uncultivated vegetation. The UAV SenseFly, equipped with a camera Canon Ixus 220HS, flew autonomously over the area at a height of 130 m yielding a block of 49 images divided in 5 strips. Sixteen pre-signalized Ground Control Points, surveyed in the area through GPS (NRTK survey), allowed the referencing of the block and accuracy analyses. Approximate values for exterior orientation parameters (positions and attitudes) were recorded by the flight control system. The block was processed with several software: Erdas-LPS, EyeDEA (Univ. of Parma), Agisoft Photoscan, Pix4UAV, in assisted or automatic way. Results comparisons are given in terms of differences among digital surface models, differences in orientation parameters and accuracies, when available. Moreover, image and ground point coordinates obtained by the various software were independently used as initial values in a comparative adjustment made by scientific in-house software, which can apply constraints to evaluate the effectiveness of different methods of point extraction and accuracies on ground check points.

An Analysis of the Influence of Flight Parameters in the Generation of Unmanned Aerial Vehicle (UAV) Orthomosaicks to Survey Archaeological Areas.

PubMed

Mesas-Carrascosa, Francisco-Javier; Notario García, María Dolores; Meroño de Larriva, Jose Emilio; García-Ferrer, Alfonso

2016-11-01

This article describes the configuration and technical specifications of a multi-rotor unmanned aerial vehicle (UAV) using a red-green-blue (RGB) sensor for the acquisition of images needed for the production of orthomosaics to be used in archaeological applications. Several flight missions were programmed as follows: flight altitudes at 30, 40, 50, 60, 70 and 80 m above ground level; two forward and side overlap settings (80%-50% and 70%-40%); and the use, or lack thereof, of ground control points. These settings were chosen to analyze their influence on the spatial quality of orthomosaicked images processed by Inpho UASMaster (Trimble, CA, USA). Changes in illumination over the study area, its impact on flight duration, and how it relates to these settings is also considered. The combined effect of these parameters on spatial quality is presented as well, defining a ratio between ground sample distance of UAV images and expected root mean square of a UAV orthomosaick. The results indicate that a balance between all the proposed parameters is useful for optimizing mission planning and image processing, altitude above ground level (AGL) being main parameter because of its influence on root mean square error (RMSE).

An Analysis of the Influence of Flight Parameters in the Generation of Unmanned Aerial Vehicle (UAV) Orthomosaicks to Survey Archaeological Areas

PubMed Central

Mesas-Carrascosa, Francisco-Javier; Notario García, María Dolores; Meroño de Larriva, Jose Emilio; García-Ferrer, Alfonso

2016-01-01

This article describes the configuration and technical specifications of a multi-rotor unmanned aerial vehicle (UAV) using a red–green–blue (RGB) sensor for the acquisition of images needed for the production of orthomosaics to be used in archaeological applications. Several flight missions were programmed as follows: flight altitudes at 30, 40, 50, 60, 70 and 80 m above ground level; two forward and side overlap settings (80%–50% and 70%–40%); and the use, or lack thereof, of ground control points. These settings were chosen to analyze their influence on the spatial quality of orthomosaicked images processed by Inpho UASMaster (Trimble, CA, USA). Changes in illumination over the study area, its impact on flight duration, and how it relates to these settings is also considered. The combined effect of these parameters on spatial quality is presented as well, defining a ratio between ground sample distance of UAV images and expected root mean square of a UAV orthomosaick. The results indicate that a balance between all the proposed parameters is useful for optimizing mission planning and image processing, altitude above ground level (AGL) being main parameter because of its influence on root mean square error (RMSE). PMID:27809293

Optimal Path Planning and Control of Quadrotor Unmanned Aerial Vehicle for Area Coverage

NASA Astrophysics Data System (ADS)

Fan, Jiankun

An Unmanned Aerial Vehicle (UAV) is an aircraft without a human pilot on board. Its flight is controlled either autonomously by computers onboard the vehicle, or remotely by a pilot on the ground, or by another vehicle. In recent years, UAVs have been used more commonly than prior years. The example includes areo-camera where a high speed camera was attached to a UAV which can be used as an airborne camera to obtain aerial video. It also could be used for detecting events on ground for tasks such as surveillance and monitoring which is a common task during wars. Similarly UAVs can be used for relaying communication signal during scenarios when regular communication infrastructure is destroyed. The objective of this thesis is motivated from such civilian operations such as search and rescue or wildfire detection and monitoring. One scenario is that of search and rescue where UAV's objective is to geo-locate a person in a given area. The task is carried out with the help of a camera whose live feed is provided to search and rescue personnel. For this objective, the UAV needs to carry out scanning of the entire area in the shortest time. The aim of this thesis to develop algorithms to enable a UAV to scan an area in optimal time, a problem referred to as "Coverage Control" in literature. The thesis focuses on a special kind of UAVs called "quadrotor" that is propelled with the help of four rotors. The overall objective of this thesis is achieved via solving two problems. The first problem is to develop a dynamic control model of quadrtor. In this thesis, a proportional-integral-derivative controller (PID) based feedback control system is developed and implemented on MATLAB's Simulink. The PID controller helps track any given trajectory. The second problem is to design a trajectory that will fulfill the mission. The planed trajectory should make sure the quadrotor will scan the whole area without missing any part to make sure that the quadrotor will find the lost person in the area. The generated trajectory should also be optimal. This is achieved via making some assumptions on the form of the trajectory and solving the optimization problem to obtain optimal parameters of the trajectory. The proposed techniques are validated with the help of numerous simulations.

Evaluating the accuracy of low cost UAV generated topography and its effectiveness for geomorphic change detection

NASA Astrophysics Data System (ADS)

Cook, Kristen

2015-04-01

With the recent explosion in the use and availability of unmanned aerial vehicle platforms and development of easy to use structure from motion (SfM) software, UAV based photogrammetry is increasingly being adopted to produce high resolution topography for the study of surface processes. UAV systems can vary substantially in price and complexity, but the tradeoffs between these and the quality of the resulting data are not well constrained. We look at one end of this spectrum and evaluate the effectiveness of a simple low cost UAV setup for obtaining high resolution topography in a challenging field setting. Our study site is the Daan River gorge in western Taiwan, a rapidly eroding bedrock gorge that we have monitored with terrestrial Lidar since 2009. The site presents challenges for the generation and analysis of high resolution topography, including vertical gorge walls, vegetation, wide variation in surface roughness, and a complicated 3D morphology. In order to evaluate the accuracy of the UAV-derived topography, we compare it with terrestrial Lidar data collected during the same survey period. Our UAV setup combines a DJI Phantom 2 quadcopter with a 16 megapixel Canon Powershot camera for a total platform cost of less than 850. The quadcopter is flown manually, and the camera is programmed to take a photograph every 4 seconds, yielding 200-250 pictures per flight. We measured ground control points and targets for both the Lidar scans and the aerial surveys using a Leica RTK GPS with 1-2 cm accuracy. UAV derived point clouds were obtained using Agisoft Photoscan software. We conducted both Lidar and UAV surveys before and after the 2014 typhoon season, allowing us to evaluate the reliability of the UAV survey to detect geomorphic changes in the range of one to several meters. The accuracy of the SfM point clouds depends strongly on the characteristics of the surface being considered, with vegetation and small scale texture causing inaccuracies. However, we find that this simple UAV setup can yield point clouds with 78% of points within 20 cm and 60% within 10 cm of the Lidar point clouds, with the higher errors dominated by vegetation effects. Well-distributed and accurately located ground control points are critical, but we achieve good accuracy with even with relatively few ground control points (25) over a 150,000 sq m area. The large number of photographs taken during each flight also allows us to explore the reproducibility of the UAV-derived topography by generating point clouds from different subsets of photographs taken of the same area during a single survey. These results show the same pattern of higher errors due to vegetation, but bedrock surfaces generally have errors of less than 4 cm. These results suggest that even very basic UAV surveys can yield data suitable for measuring geomorphic change on the scale of a channel reach.

Seabird species vary in behavioural response to drone census.

PubMed

Brisson-Curadeau, Émile; Bird, David; Burke, Chantelle; Fifield, David A; Pace, Paul; Sherley, Richard B; Elliott, Kyle H

2017-12-20

Unmanned aerial vehicles (UAVs) provide an opportunity to rapidly census wildlife in remote areas while removing some of the hazards. However, wildlife may respond negatively to the UAVs, thereby skewing counts. We surveyed four species of Arctic cliff-nesting seabirds (glaucous gull Larus hyperboreus, Iceland gull Larus glaucoides, common murre Uria aalge and thick-billed murre Uria lomvia) using a UAV and compared censusing techniques to ground photography. An average of 8.5% of murres flew off in response to the UAV, but >99% of those birds were non-breeders. We were unable to detect any impact of the UAV on breeding success of murres, except at a site where aerial predators were abundant and several birds lost their eggs to predators following UAV flights. Furthermore, we found little evidence for habituation by murres to the UAV. Most gulls flew off in response to the UAV, but returned to the nest within five minutes. Counts of gull nests and adults were similar between UAV and ground photography, however the UAV detected up to 52.4% more chicks because chicks were camouflaged and invisible to ground observers. UAVs provide a less hazardous and potentially more accurate method for surveying wildlife. We provide some simple recommendations for their use.

Atmospheric Radiation Measurement Program facilities newsletter, January 2000

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sisterson, D.L.

2000-02-16

The subject of this newsletter is the ARM unmanned aerospace vehicle program. The ARM Program's focus is on climate research, specifically research related to solar radiation and its interaction with clouds. The SGP CART site contains highly sophisticated surface instrumentation, but even these instruments cannot gather some crucial climate data from high in the atmosphere. The Department of Energy and the Department of Defense joined together to use a high-tech, high-altitude, long-endurance class of unmanned aircraft known as the unmanned aerospace vehicle (UAV). A UAV is a small, lightweight airplane that is controlled remotely from the ground. A pilot sitsmore » in a ground-based cockpit and flies the aircraft as if he were actually on board. The UAV can also fly completely on its own through the use of preprogrammed computer flight routines. The ARM UAV is fitted with payload instruments developed to make highly accurate measurements of atmospheric flux, radiance, and clouds. Using a UAV is beneficial to climate research in many ways. The UAV puts the instrumentation within the environment being studied and gives scientists direct measurements, in contrast to indirect measurements from satellites orbiting high above Earth. The data collected by UAVs can be used to verify and calibrate measurements and calculated values from satellites, therefore making satellite data more useful and valuable to researchers.« less

UAV Cooperation Architectures for Persistent Sensing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roberts, R S; Kent, C A; Jones, E D

2003-03-20

With the number of small, inexpensive Unmanned Air Vehicles (UAVs) increasing, it is feasible to build multi-UAV sensing networks. In particular, by using UAVs in conjunction with unattended ground sensors, a degree of persistent sensing can be achieved. With proper UAV cooperation algorithms, sensing is maintained even though exceptional events, e.g., the loss of a UAV, have occurred. In this paper a cooperation technique that allows multiple UAVs to perform coordinated, persistent sensing with unattended ground sensors over a wide area is described. The technique automatically adapts the UAV paths so that on the average, the amount of time thatmore » any sensor has to wait for a UAV revisit is minimized. We also describe the Simulation, Tactical Operations and Mission Planning (STOMP) software architecture. This architecture is designed to help simulate and operate distributed sensor networks where multiple UAVs are used to collect data.« less

Formation Flight of Multiple UAVs via Onboard Sensor Information Sharing.

PubMed

Park, Chulwoo; Cho, Namhoon; Lee, Kyunghyun; Kim, Youdan

2015-07-17

To monitor large areas or simultaneously measure multiple points, multiple unmanned aerial vehicles (UAVs) must be flown in formation. To perform such flights, sensor information generated by each UAV should be shared via communications. Although a variety of studies have focused on the algorithms for formation flight, these studies have mainly demonstrated the performance of formation flight using numerical simulations or ground robots, which do not reflect the dynamic characteristics of UAVs. In this study, an onboard sensor information sharing system and formation flight algorithms for multiple UAVs are proposed. The communication delays of radiofrequency (RF) telemetry are analyzed to enable the implementation of the onboard sensor information sharing system. Using the sensor information sharing, the formation guidance law for multiple UAVs, which includes both a circular and close formation, is designed. The hardware system, which includes avionics and an airframe, is constructed for the proposed multi-UAV platform. A numerical simulation is performed to demonstrate the performance of the formation flight guidance and control system for multiple UAVs. Finally, a flight test is conducted to verify the proposed algorithm for the multi-UAV system.

Formation Flight of Multiple UAVs via Onboard Sensor Information Sharing

PubMed Central

Park, Chulwoo; Cho, Namhoon; Lee, Kyunghyun; Kim, Youdan

2015-01-01

To monitor large areas or simultaneously measure multiple points, multiple unmanned aerial vehicles (UAVs) must be flown in formation. To perform such flights, sensor information generated by each UAV should be shared via communications. Although a variety of studies have focused on the algorithms for formation flight, these studies have mainly demonstrated the performance of formation flight using numerical simulations or ground robots, which do not reflect the dynamic characteristics of UAVs. In this study, an onboard sensor information sharing system and formation flight algorithms for multiple UAVs are proposed. The communication delays of radiofrequency (RF) telemetry are analyzed to enable the implementation of the onboard sensor information sharing system. Using the sensor information sharing, the formation guidance law for multiple UAVs, which includes both a circular and close formation, is designed. The hardware system, which includes avionics and an airframe, is constructed for the proposed multi-UAV platform. A numerical simulation is performed to demonstrate the performance of the formation flight guidance and control system for multiple UAVs. Finally, a flight test is conducted to verify the proposed algorithm for the multi-UAV system. PMID:26193281

Wireless Command-and-Control of UAV-Based Imaging LANs

NASA Technical Reports Server (NTRS)

Herwitz, Stanley; Dunagan, S. E.; Sullivan, D. V.; Slye, R. E.; Leung, J. G.; Johnson, L. F.

2006-01-01

Dual airborne imaging system networks were operated using a wireless line-of-sight telemetry system developed as part of a 2002 unmanned aerial vehicle (UAV) imaging mission over the USA s largest coffee plantation on the Hawaiian island of Kauai. A primary mission objective was the evaluation of commercial-off-the-shelf (COTS) 802.11b wireless technology for reduction of payload telemetry costs associated with UAV remote sensing missions. Predeployment tests with a conventional aircraft demonstrated successful wireless broadband connectivity between a rapidly moving airborne imaging local area network (LAN) and a fixed ground station LAN. Subsequently, two separate LANs with imaging payloads, packaged in exterior-mounted pressure pods attached to the underwing of NASA's Pathfinder-Plus UAV, were operated wirelessly by ground-based LANs over independent Ethernet bridges. Digital images were downlinked from the solar-powered aircraft at data rates of 2-6 megabits per second (Mbps) over a range of 6.5 9.5 km. An integrated wide area network enabled payload monitoring and control through the Internet from a range of ca. 4000 km during parts of the mission. The recent advent of 802.11g technology is expected to boost the system data rate by about a factor of five.

Swarming Unmanned Aerial Vehicles (UAVS): Extending Marine Aviation Ground Task Force Communications Using UAVS

DTIC Science & Technology

2015-03-02

balloons , large UAVs, and satellite communications are all employed to mitigate LOS and OTH communication on the battlefield. The Marine Corps’ fleets...Phang, N. S. (2006). Tethered operation of autonomous aerial vehicles to provide extended fields of view for autonomous ground vehicles (Master’s

Multisensor Equipped Uav/ugv for Automated Exploration

NASA Astrophysics Data System (ADS)

Batzdorfer, S.; Bobbe, M.; Becker, M.; Harms, H.; Bestmann, U.

2017-08-01

The usage of unmanned systems for exploring disaster scenarios has become more and more important in recent times as a supporting system for action forces. These systems have to offer a well-balanced relationship between the quality of support and additional workload. Therefore within the joint research project ANKommEn - german acronym for Automated Navigation and Communication for Exploration - a system for exploration of disaster scenarios is build-up using multiple UAV und UGV controlled via a central ground station. The ground station serves as user interface for defining missions and tasks conducted by the unmanned systems, equipped with different environmental sensors like cameras - RGB as well as IR - or LiDAR. Depending on the exploration task results, in form of pictures, 2D stitched orthophoto or LiDAR point clouds will be transmitted via datalinks and displayed online at the ground station or will be processed in short-term after a mission, e.g. 3D photogrammetry. For mission planning and its execution, UAV/UGV monitoring and georeferencing of environmental sensor data, reliable positioning and attitude information is required. This is gathered using an integrated GNSS/IMU positioning system. In order to increase availability of positioning information in GNSS challenging scenarios, a GNSS-Multiconstellation based approach is used, amongst others. The present paper focuses on the overall system design including the ground station and sensor setups on the UAVs and UGVs, the underlying positioning techniques as well as 2D and 3D exploration based on a RGB camera mounted on board the UAV and its evaluation based on real world field tests.

Using Distance Sensors to Perform Collision Avoidance Maneuvres on Uav Applications

NASA Astrophysics Data System (ADS)

Raimundo, A.; Peres, D.; Santos, N.; Sebastião, P.; Souto, N.

2017-08-01

The Unmanned Aerial Vehicles (UAV) and its applications are growing for both civilian and military purposes. The operability of an UAV proved that some tasks and operations can be done easily and at a good cost-efficiency ratio. Nowadays, an UAV can perform autonomous missions. It is very useful to certain UAV applications, such as meteorology, vigilance systems, agriculture, environment mapping and search and rescue operations. One of the biggest problems that an UAV faces is the possibility of collision with other objects in the flight area. To avoid this, an algorithm was developed and implemented in order to prevent UAV collision with other objects. "Sense and Avoid" algorithm was developed as a system for UAVs to avoid objects in collision course. This algorithm uses a Light Detection and Ranging (LiDAR), to detect objects facing the UAV in mid-flights. This light sensor is connected to an on-board hardware, Pixhawk's flight controller, which interfaces its communications with another hardware: Raspberry Pi. Communications between Ground Control Station and UAV are made via Wi-Fi or cellular third or fourth generation (3G/4G). Some tests were made in order to evaluate the "Sense and Avoid" algorithm's overall performance. These tests were done in two different environments: A 3D simulated environment and a real outdoor environment. Both modes worked successfully on a simulated 3D environment, and "Brake" mode on a real outdoor, proving its concepts.

Employing UAVs to Acquire Detailed Vegetation and Bare Ground Data for Assessing Rangeland Health

NASA Astrophysics Data System (ADS)

Rango, A.; Laliberte, A.; Herrick, J. E.; Winters, C.

2007-12-01

Because of its value as a historical record (extending back to the mid 1930s), aerial photography is an important tool used in many rangeland studies. However, these historical photos are not very useful for detailed analysis of rangeland health because of inadequate spatial resolution and scheduling limitations. These issues are now being resolved by using Unmanned Aerial Vehicles (UAVs) over rangeland study areas. Spatial resolution improvements have been rapid in the last 10 years from the QuickBird satellite through improved aerial photography to the new UAV coverage and have utilized improved sensors and the more simplistic approach of low altitude flights. Our rangeland health experiments have shown that the low altitude UAV digital photography is preferred by rangeland scientists because it allows, for the first time, their identification of vegetation and land surface patterns and patches, gap sizes, bare soil percentages, and vegetation type. This hyperspatial imagery (imagery with a resolution finer than the object of interest) is obtained at about 5cm resolution by flying at an altitude of 150m above the surface of the Jornada Experimental Range in southern New Mexico. Additionally, the UAV provides improved temporal flexibility, such as flights immediately following fires, floods, and other catastrophic disturbances, because the flight capability is located near the study area and the vehicles are under the direct control of the users, eliminating the additional steps associated with budgets and contracts. There are significant challenges to improve the data to make them useful for operational agencies, namely, image distortion with inexpensive, consumer grade digital cameras, difficulty in detecting sufficient ground control points in small scenes (152m by 114m), accuracy of exterior UAV information on X,Y, Z, roll, pitch, and heading, the sheer number of images collected, and developing reliable relationships with ground-based data across a broad range of topographies and plant communities. Our efforts are currently focused on developing a complete and efficient workflow for UAV operational missions consisting of flight planning, image acquisition, image rectification and mosaicking, and image classification. The remote sensing capability is being incorporated into existing rangeland health assessment and monitoring protocols.

Research on fast algorithm of small UAV navigation in non-linear matrix reductionism method

NASA Astrophysics Data System (ADS)

Zhang, Xiao; Fang, Jiancheng; Sheng, Wei; Cao, Juanjuan

2008-10-01

The low Reynolds numbers of small UAV will result in unfavorable aerodynamic conditions to support controlled flight. And as operated near ground, the small UAV will be affected seriously by low-frequency interference caused by atmospheric disturbance. Therefore, the GNC system needs high frequency of attitude estimation and control to realize the steady of the UAV. In company with the dimensional of small UAV dwindling away, its GNC system is more and more taken embedded designing technology to reach the purpose of compactness, light weight and low power consumption. At the same time, the operational capability of GNC system also gets limit in a certain extent. Therefore, a kind of high speed navigation algorithm design becomes the imminence demand of GNC system. Aiming at such requirement, a kind of non-linearity matrix reduction approach is adopted in this paper to create a new high speed navigation algorithm which holds the radius of meridian circle and prime vertical circle as constant and linearizes the position matrix calculation formulae of navigation equation. Compared with normal navigation algorithm, this high speed navigation algorithm decreases 17.3% operand. Within small UAV"s mission radius (20km), the accuracy of position error is less than 0.13m. The results of semi-physical experiments and small UAV's auto pilot testing proved that this algorithm can realize high frequency attitude estimation and control. It will avoid low-frequency interference caused by atmospheric disturbance properly.

UAV field demonstration of social media enabled tactical data link

NASA Astrophysics Data System (ADS)

Olson, Christopher C.; Xu, Da; Martin, Sean R.; Castelli, Jonathan C.; Newman, Andrew J.

2015-05-01

This paper addresses the problem of enabling Command and Control (C2) and data exfiltration functions for missions using small, unmanned, airborne surveillance and reconnaissance platforms. The authors demonstrated the feasibility of using existing commercial wireless networks as the data transmission infrastructure to support Unmanned Aerial Vehicle (UAV) autonomy functions such as transmission of commands, imagery, metadata, and multi-vehicle coordination messages. The authors developed and integrated a C2 Android application for ground users with a common smart phone, a C2 and data exfiltration Android application deployed on-board the UAVs, and a web server with database to disseminate the collected data to distributed users using standard web browsers. The authors performed a mission-relevant field test and demonstration in which operators commanded a UAV from an Android device to search and loiter; and remote users viewed imagery, video, and metadata via web server to identify and track a vehicle on the ground. Social media served as the tactical data link for all command messages, images, videos, and metadata during the field demonstration. Imagery, video, and metadata were transmitted from the UAV to the web server via multiple Twitter, Flickr, Facebook, YouTube, and similar media accounts. The web server reassembled images and video with corresponding metadata for distributed users. The UAV autopilot communicated with the on-board Android device via on-board Bluetooth network.

Unmanned Aerial Vehicles unique cost estimating requirements

NASA Astrophysics Data System (ADS)

Malone, P.; Apgar, H.; Stukes, S.; Sterk, S.

Unmanned Aerial Vehicles (UAVs), also referred to as drones, are aerial platforms that fly without a human pilot onboard. UAVs are controlled autonomously by a computer in the vehicle or under the remote control of a pilot stationed at a fixed ground location. There are a wide variety of drone shapes, sizes, configurations, complexities, and characteristics. Use of these devices by the Department of Defense (DoD), NASA, civil and commercial organizations continues to grow. UAVs are commonly used for intelligence, surveillance, reconnaissance (ISR). They are also use for combat operations, and civil applications, such as firefighting, non-military security work, surveillance of infrastructure (e.g. pipelines, power lines and country borders). UAVs are often preferred for missions that require sustained persistence (over 4 hours in duration), or are “ too dangerous, dull or dirty” for manned aircraft. Moreover, they can offer significant acquisition and operations cost savings over traditional manned aircraft. Because of these unique characteristics and missions, UAV estimates require some unique estimating methods. This paper describes a framework for estimating UAV systems total ownership cost including hardware components, software design, and operations. The challenge of collecting data, testing the sensitivities of cost drivers, and creating cost estimating relationships (CERs) for each key work breakdown structure (WBS) element is discussed. The autonomous operation of UAVs is especially challenging from a software perspective.

Comparison of a UAV-derived point-cloud to Lidar data at Haig Glacier, Alberta, Canada

NASA Astrophysics Data System (ADS)

Bash, E. A.; Moorman, B.; Montaghi, A.; Menounos, B.; Marshall, S. J.

2016-12-01

The use of unmanned aerial vehicles (UAVs) is expanding rapidly in glaciological research as a result of technological improvements that make UAVs a cost-effective solution for collecting high resolution datasets with relative ease. The cost and difficult access traditionally associated with performing fieldwork in glacial environments makes UAVs a particularly attractive tool. In the small, but growing, body of literature using UAVs in glaciology the accuracy of UAV data is tested through the comparison of a UAV-derived DEM to measured control points. A field campaign combining simultaneous lidar and UAV flights over Haig Glacier in April 2015, provided the unique opportunity to directly compare UAV data to lidar. The UAV was a six-propeller Mikrokopter carrying a Panasonic Lumix DMC-GF1 camera with a 12 Megapixel Live MOS sensor and Lumix G 20 mm lens flown at a height of 90 m, resulting in sub-centimetre ground resolution per image pixel. Lidar data collection took place April 20, while UAV flights were conducted April 20-21. A set of 65 control points were laid out and surveyed on the glacier surface on April 19 and 21 using a RTK GPS with a vertical uncertainty of 5 cm. A direct comparison of lidar points to these control points revealed a 9 cm offset between the control points and the lidar points on average, but the difference changed distinctly from points collected on April 19 versus those collected April 21 (7 cm and 12 cm). Agisoft Photoscan was used to create a point-cloud from imagery collected with the UAV and CloudCompare was used to calculate the difference between this and the lidar point cloud, revealing an average difference of less than 17 cm. This field campaign also highlighted some of the benefits and drawbacks of using a rotary UAV for glaciological research. The vertical takeoff and landing capabilities, combined with quick responsiveness and higher carrying capacity, make the rotary vehicle favourable for high-resolution photos when working in mountainous terrain. Battery life is limited, however, compared to fixed-wing vehicles, making it more difficult to cover large areas in a short time. This analysis shows that UAVs are able to fill an important role in the future of glaciological research, when research goals are balanced with instrument accuracy and UAV platform selection.

Adaptation of Dubins Paths for UAV Ground Obstacle Avoidance When Using a Low Cost On-Board GNSS Sensor.

PubMed

Kikutis, Ramūnas; Stankūnas, Jonas; Rudinskas, Darius; Masiulionis, Tadas

2017-09-28

Current research on Unmanned Aerial Vehicles (UAVs) shows a lot of interest in autonomous UAV navigation. This interest is mainly driven by the necessity to meet the rules and restrictions for small UAV flights that are issued by various international and national legal organizations. In order to lower these restrictions, new levels of automation and flight safety must be reached. In this paper, a new method for ground obstacle avoidance derived by using UAV navigation based on the Dubins paths algorithm is presented. The accuracy of the proposed method has been tested, and research results have been obtained by using Software-in-the-Loop (SITL) simulation and real UAV flights, with the measurements done with a low cost Global Navigation Satellite System (GNSS) sensor. All tests were carried out in a three-dimensional space, but the height accuracy was not assessed. The GNSS navigation data for the ground obstacle avoidance algorithm is evaluated statistically.

Adaptation of Dubins Paths for UAV Ground Obstacle Avoidance When Using a Low Cost On-Board GNSS Sensor

PubMed Central

Kikutis, Ramūnas; Stankūnas, Jonas; Rudinskas, Darius; Masiulionis, Tadas

2017-01-01

Current research on Unmanned Aerial Vehicles (UAVs) shows a lot of interest in autonomous UAV navigation. This interest is mainly driven by the necessity to meet the rules and restrictions for small UAV flights that are issued by various international and national legal organizations. In order to lower these restrictions, new levels of automation and flight safety must be reached. In this paper, a new method for ground obstacle avoidance derived by using UAV navigation based on the Dubins paths algorithm is presented. The accuracy of the proposed method has been tested, and research results have been obtained by using Software-in-the-Loop (SITL) simulation and real UAV flights, with the measurements done with a low cost Global Navigation Satellite System (GNSS) sensor. All tests were carried out in a three-dimensional space, but the height accuracy was not assessed. The GNSS navigation data for the ground obstacle avoidance algorithm is evaluated statistically. PMID:28956839

Robust all-source positioning of UAVs based on belief propagation

NASA Astrophysics Data System (ADS)

Chen, Xi; Gao, Wenyun; Wang, Jiabo

2013-12-01

For unmanned air vehicles (UAVs) to survive hostile operational environments, it is always preferable to utilize all wireless positioning sources available to fuse a robust position. While belief propagation is a well-established method for all source data fusion, it is not an easy job to handle all the mathematics therein. In this work, a comprehensive mathematical framework for belief propagation-based all-source positioning of UAVs is developed, taking wireless sources including Global Navigation Satellite Systems (GNSS) space vehicles, peer UAVs, ground control stations, and signal of opportunities. Based on the mathematical framework, a positioning algorithm named Belief propagation-based Opportunistic Positioning of UAVs (BOPU) is proposed, with an unscented particle filter for Bayesian approximation. The robustness of the proposed BOPU is evaluated by a fictitious scenario that a group of formation flying UAVs encounter GNSS countermeasures en route. Four different configurations of measurements availability are simulated. The results show that the performance of BOPU varies only slightly with different measurements availability.

Precision wildlife monitoring using unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Hodgson, Jarrod C.; Baylis, Shane M.; Mott, Rowan; Herrod, Ashley; Clarke, Rohan H.

2016-03-01

Unmanned aerial vehicles (UAVs) represent a new frontier in environmental research. Their use has the potential to revolutionise the field if they prove capable of improving data quality or the ease with which data are collected beyond traditional methods. We apply UAV technology to wildlife monitoring in tropical and polar environments and demonstrate that UAV-derived counts of colony nesting birds are an order of magnitude more precise than traditional ground counts. The increased count precision afforded by UAVs, along with their ability to survey hard-to-reach populations and places, will likely drive many wildlife monitoring projects that rely on population counts to transition from traditional methods to UAV technology. Careful consideration will be required to ensure the coherence of historic data sets with new UAV-derived data and we propose a method for determining the number of duplicated (concurrent UAV and ground counts) sampling points needed to achieve data compatibility.

Vision-Based Precision Landings of a Tailsitter UAV

DTIC Science & Technology

2010-04-01

2.2: Schematic of the controller used in simulation. The block diagram shown in Figure 2.2 shows the simulation structure used to simulate the vision...the structure of the flight facility walls, any vibration applied to the structure would potentially change the pose of the cameras. Each camera’s pose...relative to the target in Chap- ter 4, a flat earth assumption was made. In several situations the approximation that the ground over which the UAV is

Colour-based Object Detection and Tracking for Autonomous Quadrotor UAV

NASA Astrophysics Data System (ADS)

Kadouf, Hani Hunud A.; Mohd Mustafah, Yasir

2013-12-01

With robotics becoming a fundamental aspect of modern society, further research and consequent application is ever increasing. Aerial robotics, in particular, covers applications such as surveillance in hostile military zones or search and rescue operations in disaster stricken areas, where ground navigation is impossible. The increased visual capacity of UAV's (Unmanned Air Vehicles) is also applicable in the support of ground vehicles to provide supplies for emergency assistance, for scouting purposes or to extend communication beyond insurmountable land or water barriers. The Quadrotor, which is a small UAV has its lift generated by four rotors and can be controlled by altering the speeds of its motors relative to each other. The four rotors allow for a higher payload than single or dual rotor UAVs, which makes it safer and more suitable to carry camera and transmitter equipment. An onboard camera is used to capture and transmit images of the Quadrotor's First Person View (FPV) while in flight, in real time, wirelessly to a base station. The aim of this research is to develop an autonomous quadrotor platform capable of transmitting real time video signals to a base station for processing. The result from the image analysis will be used as a feedback in the quadrotor positioning control. To validate the system, the algorithm should have the capacity to make the quadrotor identify, track or hover above stationary or moving objects.

Concept and realization of unmanned aerial system with different modes of operation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Czyba, Roman; Szafrański, Grzegorz; Janusz, Wojciech

2014-12-10

In this paper we describe the development process of unmanned aerial system, its mechanical components, electronics and software solutions. During the stage of design, we have formulated some necessary requirements for the multirotor vehicle and ground control station in order to build an optimal system which can be used for the reconnaissance missions. Platform is controlled by use of the ground control station (GCS) and has possibility of accomplishing video based observation tasks. In order to fulfill this requirement the on-board payload consists of mechanically stabilized camera augmented with machine vision algorithms to enable object tracking tasks. Novelty of themore » system are four modes of flight, which give full functionality of the developed UAV system. Designed ground control station is consisted not only of the application itself, but also a built-in dedicated components located inside the chassis, which together creates an advanced UAV system supporting the control and management of the flight. Mechanical part of quadrotor is designed to ensure its robustness while meeting objectives of minimizing weight of the platform. Finally the designed electronics allows for implementation of control and estimation algorithms without the needs for their excessive computational optimization.« less

The development of a UGV-mounted automated refueling system for VTOL UAVs

NASA Astrophysics Data System (ADS)

Wills, Mike; Burmeister, Aaron; Nelson, Travis; Denewiler, Thomas; Mullens, Kathy

2006-05-01

This paper describes the latest efforts to develop an Automated UAV Mission System (AUMS) for small vertical takeoff and landing (VTOL) unmanned air vehicles (UAVs). In certain applications such as force protection, perimeter security, and urban surveillance a VTOL UAV can provide far greater utility than fixed-wing UAVs or ground-based sensors. The VTOL UAV can operate much closer to an object of interest and can provide a hover-and-stare capability to keep its sensors trained on an object, while the fixed wing UAV would be forced into a higher altitude loitering pattern where its sensors would be subject to intermittent blockage by obstacles and terrain. The most significant disadvantage of a VTOL UAV when compared to a fixed-wing UAV is its reduced flight endurance. AUMS addresses this disadvantage by providing forward staging, refueling, and recovery capabilities for the VTOL UAV through a host unmanned ground vehicle (UGV), which serves as a launch/recovery platform and service station. The UGV has sufficient payload capacity to carry UAV fuel for multiple launch, recovery, and refuel iterations. The UGV also provides a highly mobile means of forward deploying a small UAV into hazardous areas unsafe for personnel, such as chemically or biologically contaminated areas. Teaming small UAVs with large UGVs can decrease risk to personnel and expand mission capabilities and effectiveness. There are numerous technical challenges being addressed by these development efforts. Among the challenges is the development and integration of a precision landing system compact and light enough to allow it to be mounted on a small VTOL UAV while providing repeatable landing accuracy to safely land on the AUMS. Another challenge is the design of a UGV-transportable, expandable, self-centering landing pad that contains hardware and safety devices for automatically refueling the UAV. A third challenge is making the design flexible enough to accommodate different types of VTOL UAVs, such as the AAI iSTAR ducted-fan vehicle and small helicopter UAVs. Finally, a common command-and-control architecture which supports the UAV, UGV, and AUMS must be developed and interfaced with these systems to allow fully autonomous collaborative behaviors. Funded by the Joint Robotics Program, AUMS is part of a joint effort with the Air Force Research Laboratory and the Army Missile Research Development and Engineering Command. The objective is to develop and demonstrate UGVUAV teaming concepts and work with the warfighter to ensure that future upgrades are focused on operational requirements. This paper describes the latest achievements in AUMS development and some of the military program and first responder situations that could benefit from this system.

Field Accuracy Test of Rpas Photogrammetry

NASA Astrophysics Data System (ADS)

Barry, P.; Coakley, R.

2013-08-01

Baseline Surveys Ltd is a company which specialises in the supply of accurate geospatial data, such as cadastral, topographic and engineering survey data to commercial and government bodies. Baseline Surveys Ltd invested in aerial drone photogrammetric technology and had a requirement to establish the spatial accuracy of the geographic data derived from our unmanned aerial vehicle (UAV) photogrammetry before marketing our new aerial mapping service. Having supplied the construction industry with survey data for over 20 years, we felt that is was crucial for our clients to clearly understand the accuracy of our photogrammetry so they can safely make informed spatial decisions, within the known accuracy limitations of our data. This information would also inform us on how and where UAV photogrammetry can be utilised. What we wanted to find out was the actual accuracy that can be reliably achieved using a UAV to collect data under field conditions throughout a 2 Ha site. We flew a UAV over the test area in a "lawnmower track" pattern with an 80% front and 80% side overlap; we placed 45 ground markers as check points and surveyed them in using network Real Time Kinematic Global Positioning System (RTK GPS). We specifically designed the ground markers to meet our accuracy needs. We established 10 separate ground markers as control points and inputted these into our photo modelling software, Agisoft PhotoScan. The remaining GPS coordinated check point data were added later in ArcMap to the completed orthomosaic and digital elevation model so we could accurately compare the UAV photogrammetry XYZ data with the RTK GPS XYZ data at highly reliable common points. The accuracy we achieved throughout the 45 check points was 95% reliably within 41 mm horizontally and 68 mm vertically and with an 11.7 mm ground sample distance taken from a flight altitude above ground level of 90 m.The area covered by one image was 70.2 m × 46.4 m, which equals 0.325 Ha. This finding has shown that XYZ data derived from UAV photogrammetry has a similar practical accuracy to RTK GPS, which is commonly used for cadastral, topographic and engineering survey work. This means that UAV photogrammetry can, for the most part, replace GPS surveying as the main method of data capture for engineering projects, boundary mapping and topographical surveying. Aerial Photogrammetry, in conjunction with RTK GPS, can now be used for projects with a 1:200 map scale accuracy requirement.

Unmanned aerial vehicle-based structure from motion biomass inventory estimates

NASA Astrophysics Data System (ADS)

Bedell, Emily; Leslie, Monique; Fankhauser, Katie; Burnett, Jonathan; Wing, Michael G.; Thomas, Evan A.

2017-04-01

Riparian vegetation restoration efforts require cost-effective, accurate, and replicable impact assessments. We present a method to use an unmanned aerial vehicle (UAV) equipped with a GoPro digital camera to collect photogrammetric data of a 0.8-ha riparian restoration. A three-dimensional point cloud was created from the photos using "structure from motion" techniques. The point cloud was analyzed and compared to traditional, ground-based monitoring techniques. Ground-truth data were collected on 6.3% of the study site and averaged across the entire site to report stem heights in stems/ha in three height classes. The project site was divided into four analysis sections, one for derivation of parameters used in the UAV data analysis and the remaining three sections reserved for method validation. Comparing the ground-truth data to the UAV generated data produced an overall error of 21.6% and indicated an R2 value of 0.98. A Bland-Altman analysis indicated a 95% probability that the UAV stems/section result will be within 61 stems/section of the ground-truth data. The ground-truth data are reported with an 80% confidence interval of ±1032 stems/ha thus, the UAV was able to estimate stems well within this confidence interval.

Study of Lever-Arm Effect Using Embedded Photogrammetry and On-Board GPS Receiver on Uav for Metrological Mapping Purpose and Proposal of a Free Ground Measurements Calibration Procedure

NASA Astrophysics Data System (ADS)

Daakir, M.; Pierrot-Deseilligny, M.; Bosser, P.; Pichard, F.; Thom, C.; Rabot, Y.

2016-03-01

Nowadays, Unmanned Aerial Vehicle (UAV) on-board photogrammetry knows a significant growth due to the democratization of using drones in the civilian sector. Also, due to changes in regulations laws governing the rules of inclusion of a UAV in the airspace which become suitable for the development of professional activities. Fields of application of photogrammetry are diverse, for instance: architecture, geology, archaeology, mapping, industrial metrology, etc. Our research concerns the latter area. Vinci-Construction- Terrassement is a private company specialized in public earthworks that uses UAVs for metrology applications. This article deals with maximum accuracy one can achieve with a coupled camera and GPS receiver system for direct-georeferencing of Digital Surface Models (DSMs) without relying on Ground Control Points (GCPs) measurements. This article focuses specially on the lever-arm calibration part. This proposed calibration method is based on two steps: a first step involves the proper calibration for each sensor, i.e. to determine the position of the optical center of the camera and the GPS antenna phase center in a local coordinate system relative to the sensor. A second step concerns a 3d modeling of the UAV with embedded sensors through a photogrammetric acquisition. Processing this acquisition allows to determine the value of the lever-arm offset without using GCPs.

Autonomous target tracking of UAVs based on low-power neural network hardware

NASA Astrophysics Data System (ADS)

Yang, Wei; Jin, Zhanpeng; Thiem, Clare; Wysocki, Bryant; Shen, Dan; Chen, Genshe

2014-05-01

Detecting and identifying targets in unmanned aerial vehicle (UAV) images and videos have been challenging problems due to various types of image distortion. Moreover, the significantly high processing overhead of existing image/video processing techniques and the limited computing resources available on UAVs force most of the processing tasks to be performed by the ground control station (GCS) in an off-line manner. In order to achieve fast and autonomous target identification on UAVs, it is thus imperative to investigate novel processing paradigms that can fulfill the real-time processing requirements, while fitting the size, weight, and power (SWaP) constrained environment. In this paper, we present a new autonomous target identification approach on UAVs, leveraging the emerging neuromorphic hardware which is capable of massively parallel pattern recognition processing and demands only a limited level of power consumption. A proof-of-concept prototype was developed based on a micro-UAV platform (Parrot AR Drone) and the CogniMemTMneural network chip, for processing the video data acquired from a UAV camera on the y. The aim of this study was to demonstrate the feasibility and potential of incorporating emerging neuromorphic hardware into next-generation UAVs and their superior performance and power advantages towards the real-time, autonomous target tracking.

Development of autonomous controller system of high speed UAV from simulation to ready to fly condition

NASA Astrophysics Data System (ADS)

Yudhi Irwanto, Herma

2018-02-01

The development of autonomous controller system that is specially used in our high speed UAV, it’s call RKX-200EDF/TJ controlled vehicle needs to be continued as a step to mastery and to developt control system of LAPAN’s satellite launching rocket. The weakness of the existing control system in this high speed UAV needs to be repaired and replaced using the autonomous controller system. Conversion steps for ready-to-fly system involved controlling X tail fin, adjusting auto take off procedure by adding X axis sensor, procedure of way points reading and process of measuring distance and heading to the nearest way point, developing user-friendly ground station, and adding tools for safety landing. The development of this autonomous controller system also covered a real flying test in Pandanwangi, Lumajang in November 2016. Unfortunately, the flying test was not successful because the booster rocket was blown right after burning. However, the system could record the event and demonstrated that the controller system had worked according to plan.

Augmented Reality Tool for the Situational Awareness Improvement of UAV Operators

PubMed Central

Ruano, Susana; Cuevas, Carlos; Gallego, Guillermo; García, Narciso

2017-01-01

Unmanned Aerial Vehicles (UAVs) are being extensively used nowadays. Therefore, pilots of traditional aerial platforms should adapt their skills to operate them from a Ground Control Station (GCS). Common GCSs provide information in separate screens: one presents the video stream while the other displays information about the mission plan and information coming from other sensors. To avoid the burden of fusing information displayed in the two screens, an Augmented Reality (AR) tool is proposed in this paper. The AR system has two functionalities for Medium-Altitude Long-Endurance (MALE) UAVs: route orientation and target identification. Route orientation allows the operator to identify the upcoming waypoints and the path that the UAV is going to follow. Target identification allows a fast target localization, even in the presence of occlusions. The AR tool is implemented following the North Atlantic Treaty Organization (NATO) standards so that it can be used in different GCSs. The experiments show how the AR tool improves significantly the situational awareness of the UAV operators. PMID:28178189

Augmented Reality Tool for the Situational Awareness Improvement of UAV Operators.

PubMed

Ruano, Susana; Cuevas, Carlos; Gallego, Guillermo; García, Narciso

2017-02-06

Unmanned Aerial Vehicles (UAVs) are being extensively used nowadays. Therefore, pilots of traditional aerial platforms should adapt their skills to operate them from a Ground Control Station (GCS). Common GCSs provide information in separate screens: one presents the video stream while the other displays information about the mission plan and information coming from other sensors. To avoid the burden of fusing information displayed in the two screens, an Augmented Reality (AR) tool is proposed in this paper. The AR system has two functionalities for Medium-Altitude Long-Endurance (MALE) UAVs: route orientation and target identification. Route orientation allows the operator to identify the upcoming waypoints and the path that the UAV is going to follow. Target identification allows a fast target localization, even in the presence of occlusions. The AR tool is implemented following the North Atlantic Treaty Organization (NATO) standards so that it can be used in different GCSs. The experiments show how the AR tool improves significantly the situational awareness of the UAV operators.

Cooperative UAV-Based Communications Backbone for Sensor Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roberts, R S

2001-10-07

The objective of this project is to investigate the use of unmanned air vehicles (UAVs) as mobile, adaptive communications backbones for ground-based sensor networks. In this type of network, the UAVs provide communication connectivity to sensors that cannot communicate with each other because of terrain, distance, or other geographical constraints. In these situations, UAVs provide a vertical communication path for the sensors, thereby mitigating geographic obstacles often imposed on networks. With the proper use of UAVs, connectivity to a widely disbursed sensor network in rugged terrain is readily achieved. Our investigation has focused on networks where multiple cooperating UAVs aremore » used to form a network backbone. The advantage of using multiple UAVs to form the network backbone is parallelization of sensor connectivity. Many widely spaced or isolated sensors can be connected to the network at once using this approach. In these networks, the UAVs logically partition the sensor network into sub-networks (subnets), with one UAV assigned per subnet. Partitioning the network into subnets allows the UAVs to service sensors in parallel thereby decreasing the sensor-to-network connectivity. A UAV services sensors in its subnet by flying a route (path) through the subnet, uplinking data collected by the sensors, and forwarding the data to a ground station. An additional advantage of using multiple UAVs in the network is that they provide redundancy in the communications backbone, so that the failure of a single UAV does not necessarily imply the loss of the network.« less

Design and development of a robust ATP subsystem for the Altair UAV-to-Ground lasercomm 2.5 Gbps demonstration

NASA Technical Reports Server (NTRS)

Ortiz, G. G.; Lee, S.; Monacos, S.; Wright, M.; Biswas, A.

2003-01-01

A robust acquisition, tracking and pointing (ATP) subsystem is being developed for the 2.5 Gigabit per second (Gbps) Unmanned-Aerial-Vehicle (UAV) to ground free-space optical communications link project.

Sensor-driven area coverage for an autonomous fixed-wing unmanned aerial vehicle.

PubMed

Paull, Liam; Thibault, Carl; Nagaty, Amr; Seto, Mae; Li, Howard

2014-09-01

Area coverage with an onboard sensor is an important task for an unmanned aerial vehicle (UAV) with many applications. Autonomous fixed-wing UAVs are more appropriate for larger scale area surveying since they can cover ground more quickly. However, their non-holonomic dynamics and susceptibility to disturbances make sensor coverage a challenging task. Most previous approaches to area coverage planning are offline and assume that the UAV can follow the planned trajectory exactly. In this paper, this restriction is removed as the aircraft maintains a coverage map based on its actual pose trajectory and makes control decisions based on that map. The aircraft is able to plan paths in situ based on sensor data and an accurate model of the on-board camera used for coverage. An information theoretic approach is used that selects desired headings that maximize the expected information gain over the coverage map. In addition, the branch entropy concept previously developed for autonomous underwater vehicles is extended to UAVs and ensures that the vehicle is able to achieve its global coverage mission. The coverage map over the workspace uses the projective camera model and compares the expected area of the target on the ground and the actual area covered on the ground by each pixel in the image. The camera is mounted on a two-axis gimbal and can either be stabilized or optimized for maximal coverage. Hardware-in-the-loop simulation results and real hardware implementation on a fixed-wing UAV show the effectiveness of the approach. By including the already developed automatic takeoff and landing capabilities, we now have a fully automated and robust platform for performing aerial imagery surveys.

Accuracy Assessment of Direct Georeferencing for Photogrammetric Applications on Small Unmanned Aerial Platforms

NASA Astrophysics Data System (ADS)

Mian, O.; Lutes, J.; Lipa, G.; Hutton, J. J.; Gavelle, E.; Borghini, S.

2016-03-01

Efficient mapping from unmanned aerial platforms cannot rely on aerial triangulation using known ground control points. The cost and time of setting ground control, added to the need for increased overlap between flight lines, severely limits the ability of small VTOL platforms, in particular, to handle mapping-grade missions of all but the very smallest survey areas. Applanix has brought its experience in manned photogrammetry applications to this challenge, setting out the requirements for increasing the efficiency of mapping operations from small UAVs, using survey-grade GNSS-Inertial technology to accomplish direct georeferencing of the platform and/or the imaging payload. The Direct Mapping Solution for Unmanned Aerial Vehicles (DMS-UAV) is a complete and ready-to-integrate OEM solution for Direct Georeferencing (DG) on unmanned aerial platforms. Designed as a solution for systems integrators to create mapping payloads for UAVs of all types and sizes, the DMS produces directly georeferenced products for any imaging payload (visual, LiDAR, infrared, multispectral imaging, even video). Additionally, DMS addresses the airframe's requirements for high-accuracy position and orientation for such tasks as precision RTK landing and Precision Orientation for Air Data Systems (ADS), Guidance and Control. This paper presents results using a DMS comprised of an Applanix APX-15 UAV with a Sony a7R camera to produce highly accurate orthorectified imagery without Ground Control Points on a Microdrones md4-1000 platform conducted by Applanix and Avyon. APX-15 UAV is a single-board, small-form-factor GNSS-Inertial system designed for use on small, lightweight platforms. The Sony a7R is a prosumer digital RGB camera sensor, with a 36MP, 4.9-micron CCD producing images at 7360 columns by 4912 rows. It was configured with a 50mm AF-S Nikkor f/1.8 lens and subsequently with a 35mm Zeiss Sonnar T* FE F2.8 lens. Both the camera/lens combinations and the APX-15 were mounted to a Microdrones md4-1000 quad-rotor VTOL UAV. The Sony A7R and each lens combination were focused and calibrated terrestrially using the Applanix camera calibration facility, and then integrated with the APX-15 GNSS-Inertial system using a custom mount specifically designed for UAV applications. The mount is constructed in such a way as to maintain the stability of both the interior orientation and IMU boresight calibration over shock and vibration, thus turning the Sony A7R into a metric imaging solution. In July and August 2015, Applanix and Avyon carried out a series of test flights of this system. The goal of these test flights was to assess the performance of DMS APX-15 direct georeferencing system under various scenarios. Furthermore, an examination of how DMS APX-15 can be used to produce accurate map products without the use of ground control points and with reduced sidelap was also carried out. Reducing the side lap for survey missions performed by small UAVs can significantly increase the mapping productivity of these platforms. The area mapped during the first flight campaign was a 250m x 300m block and a 775m long railway corridor in a rural setting in Ontario, Canada. The second area mapped was a 450m long corridor over a dam known as Fryer Dam (over Richelieu River in Quebec, Canada). Several ground control points were distributed within both test areas. The flight over the block area included 8 North-South lines and 1 cross strip flown at 80m AGL, resulting in a ~1cm GSD. The flight over the railway corridor included 2 North-South lines also flown at 80m AGL. Similarly, the flight over the dam corridor included 2 North-South lines flown at 50m AGL. The focus of this paper was to analyse the results obtained from the two corridors. Test results from both areas were processed using Direct Georeferencing techniques, and then compared for accuracy against the known positions of ground control points in each test area. The GNSS-Inertial data collected by the APX-15 was post-processed in Single Base mode, using a base station located in the project area via POSPac UAV. For the block and railway corridor, the basestation's position was precisely determined by processing a 12-hour session using the CSRS-PPP Post Processing service. Similarly, for the flight over Fryer Dam, the base-station's position was also precisely determined by processing a 4-hour session using the CSRS-PPP Post Processing service. POSPac UAV's camera calibration and quality control (CalQC) module was used to refine the camera interior orientation parameters using an Integrated Sensor Orientation (ISO) approach. POSPac UAV was also used to generate the Exterior Orientation parameters for images collected during the test flight. The Inpho photogrammetric software package was used to develop the final map products for both corridors under various scenarios. The imagery was first imported into an Inpho project, with updated focal length, principal point offsets and Exterior Orientation parameters. First, a Digital Terrain/Surface Model (DTM/DSM) was extracted from the stereo imagery, following which the raw images were orthorectified to produce an orthomosaic product.

3D acoustic atmospheric tomography

NASA Astrophysics Data System (ADS)

Rogers, Kevin; Finn, Anthony

2014-10-01

This paper presents a method for tomographically reconstructing spatially varying 3D atmospheric temperature profiles and wind velocity fields based. Measurements of the acoustic signature measured onboard a small Unmanned Aerial Vehicle (UAV) are compared to ground-based observations of the same signals. The frequency-shifted signal variations are then used to estimate the acoustic propagation delay between the UAV and the ground microphones, which are also affected by atmospheric temperature and wind speed vectors along each sound ray path. The wind and temperature profiles are modelled as the weighted sum of Radial Basis Functions (RBFs), which also allow local meteorological measurements made at the UAV and ground receivers to supplement any acoustic observations. Tomography is used to provide a full 3D reconstruction/visualisation of the observed atmosphere. The technique offers observational mobility under direct user control and the capacity to monitor hazardous atmospheric environments, otherwise not justifiable on the basis of cost or risk. This paper summarises the tomographic technique and reports on the results of simulations and initial field trials. The technique has practical applications for atmospheric research, sound propagation studies, boundary layer meteorology, air pollution measurements, analysis of wind shear, and wind farm surveys.

Unmanned Aerial Vehicle (UAV) associated DTM quality evaluation and hazard assessment

NASA Astrophysics Data System (ADS)

Huang, Mei-Jen; Chen, Shao-Der; Chao, Yu-Jui; Chiang, Yi-Lin; Chang, Kuo-Jen

2014-05-01

Taiwan, due to the high seismicity and high annual rainfall, numerous landslides triggered every year and severe impacts affect the island. Concerning to the catastrophic landslides, the key information of landslide, including range of landslide, volume estimation and the subsequent evolution are important when analyzing the triggering mechanism, hazard assessment and mitigation. Thus, the morphological analysis gives a general overview for the landslides and been considered as one of the most fundamental information. We try to integrate several technologies, especially by Unmanned Aerial Vehicle (UAV) and multi-spectral camera, to decipher the consequence and the potential hazard, and the social impact. In recent years, the remote sensing technology improves rapidly, providing a wide range of image, essential and precious information. Benefited of the advancing of informatics, remote-sensing and electric technologies, the Unmanned Aerial Vehicle (UAV) photogrammetry mas been improve significantly. The study tries to integrate several methods, including, 1) Remote-sensing images gathered by Unmanned Aerial Vehicle (UAV) and by aerial photos taken in different periods; 2) field in-situ geologic investigation; 3) Differential GPS, RTK GPS and Ground LiDAR field in-site geoinfomatics measurements; 4) Construct the DTMs before and after landslide, as well as the subsequent periods using UAV and aerial photos; 5) Discrete element method should be applied to understand the geomaterial composing the slope failure, for predicting earthquake-induced and rainfall-induced landslides displacement. First at all, we evaluate the Microdrones MD4-1000 UAV airphotos derived Digital Terrain Model (DTM). The ground resolution of the DSM point cloud of could be as high as 10 cm. By integrated 4 ground control point within an area of 56 hectares, compared with LiDAR DSM and filed RTK-GPS surveying, the mean error is as low as 6cm with a standard deviation of 17cm. The quality of the UAV DSM could be as good as LiDAR data, and is ready for other applications. The quality of the data set provides not only geoinfomatics and GIS dataset of the hazards, but also for essential geomorphologic information for other study, and for hazard mitigation and planning, as well.

Reproducibility of UAV-based earth topography reconstructions based on Structure-from-Motion algorithms

NASA Astrophysics Data System (ADS)

Clapuyt, Francois; Vanacker, Veerle; Van Oost, Kristof

2016-05-01

Combination of UAV-based aerial pictures and Structure-from-Motion (SfM) algorithm provides an efficient, low-cost and rapid framework for remote sensing and monitoring of dynamic natural environments. This methodology is particularly suitable for repeated topographic surveys in remote or poorly accessible areas. However, temporal analysis of landform topography requires high accuracy of measurements and reproducibility of the methodology as differencing of digital surface models leads to error propagation. In order to assess the repeatability of the SfM technique, we surveyed a study area characterized by gentle topography with an UAV platform equipped with a standard reflex camera, and varied the focal length of the camera and location of georeferencing targets between flights. Comparison of different SfM-derived topography datasets shows that precision of measurements is in the order of centimetres for identical replications which highlights the excellent performance of the SfM workflow, all parameters being equal. The precision is one order of magnitude higher for 3D topographic reconstructions involving independent sets of ground control points, which results from the fact that the accuracy of the localisation of ground control points strongly propagates into final results.

UAV-based remote sensing of the Heumoes landslide, Austria Vorarlberg

NASA Astrophysics Data System (ADS)

Niethammer, U.; Joswig, M.

2009-04-01

The Heumoes landslide, is located in the eastern Vorarlberg Alps, Austria, 10 km southeast of Dornbirn. The extension of the landslide is about 2000 m in west to east direction and about 500 m at its widest extent in north to south direction. It occurs between an elevation of 940 m in the east and 1360 m in the west, slope angles of more than 60 % can be observed as well as almost flat areas. Its total volume is estimated to be 9.400.000 cubic meters and its average velocities amount to some centimeter per year. Surface signatures or 'photolineations' of creeping landslides, e.g. fractures and rupture lines in sediments and street pavings, and vegetation contrasts by changes of water table in shallow vegetation in principle can be resolved by remote sensing. The necessary ground cell resolution of few centimeters, however, generally can't be achieved by routine areal or satellite imagery. The fast technological progress of unmanned areal vehicles (UAV) and the reduced payload by miniaturized optical cameras now allow for UAV remote sensing applications that are below the high financial limits of military intelligence. Even with 'low-cost' equipment, the necessary centimeter-scale ground cell resolution can be achieved by adapting the flight altitude to some ten to one hundred meters. Operated by scientists experienced in remote-control flight models, UAV remote sensing can now be performed routinely, and campaign-wise after any significant event of, e.g., heavy rainfall, or partial mudflow. We have investigated a concept of UAV-borne remote sensing based on motorized gliders, and four-propeller helicopters or 'quad-rotors'. Several missions were flown over the Heumoes landslide. Between 2006 and 2008 three series UAV-borne photographs of the Heumoes landslide were taken and could be combined to orto-mosaics of the slope area within few centimeters ground cell resolution. We will present the concept of our low cost quad-rotor UAV system and first results of the image-processing based evaluation of the acquired images to characterize spatial and temporal details of landslide behaviour. We will also sketch first schemes of joint interpretation or 'data fusion' of UAV-based remote sensing with the results from geophysical mapping of underground distribution of soil moisture and fracture processes (Walter & Joswig, EGU 2009).

A Ground-Based Near Infrared Camera Array System for UAV Auto-Landing in GPS-Denied Environment.

PubMed

Yang, Tao; Li, Guangpo; Li, Jing; Zhang, Yanning; Zhang, Xiaoqiang; Zhang, Zhuoyue; Li, Zhi

2016-08-30

This paper proposes a novel infrared camera array guidance system with capability to track and provide real time position and speed of a fixed-wing Unmanned air vehicle (UAV) during a landing process. The system mainly include three novel parts: (1) Infrared camera array and near infrared laser lamp based cooperative long range optical imaging module; (2) Large scale outdoor camera array calibration module; and (3) Laser marker detection and 3D tracking module. Extensive automatic landing experiments with fixed-wing flight demonstrate that our infrared camera array system has the unique ability to guide the UAV landing safely and accurately in real time. Moreover, the measurement and control distance of our system is more than 1000 m. The experimental results also demonstrate that our system can be used for UAV automatic accurate landing in Global Position System (GPS)-denied environments.

Applications of low-cost radio-controlled airplanes to environmental restoration at Oak Ridge National Laboratory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nyquist, J.E.

1996-10-01

The US DOE is endeavoring to clean up contamination created by the disposal of chemical and nuclear waste on the Oak Ridge Reservation (ORR), Tennessee, with an emphasis on minimizing off-site migration of contaminated surface and ground water. The task is complicated by inadequate disposal records and by the complexity of the local geology. Remote sensing data, including aerial photography and geophysics, have played an important role in the ORR site characterization. Are there advantages to collecting remote sensing data using Unmanned Aerial Vehicles (UAV`s)? In this paper, I will discuss the applications of UAV`s being explored at Oak Ridgemore » National Laboratory (ORNL) under the sponsorship of the Department of Energy`s Office of Science and technology. These applications are : aerial photography, magnetic mapping, and Very Low Frequency (VLF) electromagnetic mapping.« less

Integrating a High Resolution Optically Pumped Magnetometer with a Multi-Rotor UAV towards 3-D Magnetic Gradiometry

NASA Astrophysics Data System (ADS)

Braun, A.; Walter, C. A.; Parvar, K.

2016-12-01

The current platforms for collecting magnetic data include dense coverage, but low resolution traditional airborne surveys, and high resolution, but low coverage terrestrial surveys. Both platforms leave a critical observation gap between the ground surface and approximately 100m above ground elevation, which can be navigated efficiently by new technologies, such as Unmanned Aerial Vehicles (UAVs). Specifically, multi rotor UAV platforms provide the ability to sense the magnetic field in a full 3-D tensor, which increases the quality of data collected over other current platform types. Payload requirements and target requirements must be balanced to fully exploit the 3-D magnetic tensor. This study outlines the integration of a GEM Systems Cesium Vapour UAV Magnetometer, a Lightware SF-11 Laser Altimeter and a uBlox EVK-7P GPS module with a DJI s900 Multi Rotor UAV. The Cesium Magnetometer is suspended beneath the UAV platform by a cable of varying length. A set of surveys was carried out to optimize the sensor orientation, sensor cable length beneath the UAV and data collection methods of the GEM Systems Cesium Vapour UAV Magnetometer when mounted on the DJI s900. The target for these surveys is a 12 inch steam pipeline located approximately 2 feet below the ground surface. A systematic variation of cable length, sensor orientation and inclination was conducted. The data collected from the UAV magnetometer was compared to a terrestrial survey conducted with the GEM GST-19 Proton Procession Magnetometer at the same elevation, which also served a reference station. This allowed for a cross examination between the UAV system and a proven industry standard for magnetic field data collection. The surveys resulted in optimizing the above parameters based on minimizing instrument error and ensuring reliable data acquisition. The results demonstrate that optimizing the UAV magnetometer survey can yield to industry standard measurements.

Autonomous agricultural remote sensing systems with high spatial and temporal resolutions

NASA Astrophysics Data System (ADS)

Xiang, Haitao

In this research, two novel agricultural remote sensing (RS) systems, a Stand-alone Infield Crop Monitor RS System (SICMRS) and an autonomous Unmanned Aerial Vehicles (UAV) based RS system have been studied. A high-resolution digital color and multi-spectral camera was used as the image sensor for the SICMRS system. An artificially intelligent (AI) controller based on artificial neural network (ANN) and an adaptive neuro-fuzzy inference system (ANFIS) was developed. Morrow Plots corn field RS images in the 2004 and 2006 growing seasons were collected by the SICMRS system. The field site contained 8 subplots (9.14 m x 9.14 m) that were planted with corn and three different fertilizer treatments were used among those subplots. The raw RS images were geometrically corrected, resampled to 10cm resolution, removed soil background and calibrated to real reflectance. The RS images from two growing seasons were studied and 10 different vegetation indices were derived from each day's image. The result from the image processing demonstrated that the vegetation indices have temporal effects. To achieve high quality RS data, one has to utilize the right indices and capture the images at the right time in the growing season. Maximum variations among the image data set are within the V6-V10 stages, which indicated that these stages are the best period to identify the spatial variability caused by the nutrient stress in the corn field. The derived vegetation indices were also used to build yield prediction models via the linear regression method. At that point, all of the yield prediction models were evaluated by comparing the R2-value and the best index model from each day's image was picked based on the highest R 2-value. It was shown that the green normalized difference vegetation (GNDVI) based model is more sensitive to yield prediction than other indices-based models. During the VT-R4 stages, the GNDVI based models were able to explain more than 95% potential corn yield consistently for both seasons. The VT-R4 stages are the best period of time to estimate the corn yield. The SICMS system is only suitable for the RS research at a fixed location. In order to provide more flexibility of the RS image collection, a novel UAV based system has been studied. The UAV based agricultural RS system used a light helicopter platform equipped with a multi-spectral camera. The UAV control system consisted of an on-board and a ground station subsystem. For the on-board subsystem, an Extended Kalman Filter (EKF) based UAV navigation system was designed and implemented. The navigation system, using low cost inertial sensors, magnetometer, GPS and a single board computer, was capable of providing continuous estimates of UAV position and attitude at 50 Hz using sensor fusion techniques. The ground station subsystem was designed to be an interface between a human operator and the UAV to implement mission planning, flight command activation, and real-time flight monitoring. The navigation system is controlled by the ground station, and able to navigate the UAV in the air to reach the predefined waypoints and trigger the multi-spectral camera. By so doing, the aerial images at each point could be captured automatically. The developed UAV RS system can provide a maximum flexibility in crop field RS image collection. It is essential to perform the geometric correction and the geocoding before an aerial image can be used for precision farming. An automatic (no Ground Control Point (GCP) needed) UAV image georeferencing algorithm was developed. This algorithm can do the automatic image correction and georeferencing based on the real-time navigation data and a camera lens distortion model. The accuracy of the georeferencing algorithm was better than 90 cm according to a series test. The accuracy that has been achieved indicates that, not only is the position solution good, but the attitude error is extremely small. The waypoints planning for UAV flight was investigated. It suggested that a 16.5% forward overlap and a 15% lateral overlap were required to avoiding missing desired mapping area when the UAV flies above 45 m high with 4.5 mm lens. A whole field mosaic image can be generated according to the individual image georeferencing information. A 0.569 m mosaic error has been achieved and this accuracy is sufficient for many of the intended precision agricultural applications. With careful interpretation, the UAV images are an excellent source of high spatial and temporal resolution data for precision agricultural applications. (Abstract shortened by UMI.)

Small catchments DEM creation using Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Gafurov, A. M.

2018-01-01

Digital elevation models (DEM) are an important source of information on the terrain, allowing researchers to evaluate various exogenous processes. The higher the accuracy of DEM the better the level of the work possible. An important source of data for the construction of DEMs are point clouds obtained with terrestrial laser scanning (TLS) and unmanned aerial vehicles (UAV). In this paper, we present the results of constructing a DEM on small catchments using UAVs. Estimation of the UAV DEM showed comparable accuracy with the TLS if real time kinematic Global Positioning System (RTK-GPS) ground control points (GCPs) and check points (CPs) were used. In this case, the main source of errors in the construction of DEMs are the errors in the referencing of survey results.

Visual signature reduction of unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Zhong, Z. W.; Ma, Z. X.; Jayawijayaningtiyas; Ngoh, J. H. H.

2016-10-01

With the emergence of unmanned aerial vehicles (UAVs) in multiple tactical defence missions, there was a need for an efficient visual signature suppression system for a more efficient stealth operation. One of our studies experimentally investigated the visual signature reduction of UAVs achieved through an active camouflage system. A prototype was constructed with newly developed operating software, Cloak, to provide active camouflage to the UAV model. The reduction of visual signature was analysed. Tests of the devices mounted on UAVs were conducted in another study. A series of experiments involved testing of the concept as well as the prototype. The experiments were conducted both in the laboratory and under normal environmental conditions. Results showed certain degrees of blending with the sky to create a camouflage effect. A mini-UAV made mostly out of transparent plastic was also designed and fabricated. Because of the transparency of the plastic material, the visibility of this UAV in the air is very small, and therefore the UAV is difficult to be detected. After re-designs and tests, eventually a practical system to reduce the visibility of UAVs viewed by human observers from the ground was developed. The system was evaluated during various outdoor tests. The scene target-to-background lightness contrast and the scene target-to-background colour contrast of the adaptive control system prototype were smaller than 10% at a stand-off viewing distance of 20-50 m.

The use of unmanned aerial vehicle imagery in intertidal monitoring

NASA Astrophysics Data System (ADS)

Konar, Brenda; Iken, Katrin

2018-01-01

Intertidal monitoring projects are often limited in their practicality because traditional methods such as visual surveys or removal of biota are often limited in the spatial extent for which data can be collected. Here, we used imagery from a small unmanned aerial vehicle (sUAV) to test their potential use in rocky intertidal and intertidal seagrass surveys in the northern Gulf of Alaska. Images captured by the sUAV in the high, mid and low intertidal strata on a rocky beach and within a seagrass bed were compared to data derived concurrently from observer visual surveys and to images taken by observers on the ground. Observer visual data always resulted in the highest taxon richness, but when observer data were aggregated to the lower taxonomic resolution obtained by the sUAV images, overall community composition was mostly similar between the two methods. Ground camera images and sUAV images yielded mostly comparable community composition despite the typically higher taxonomic resolution obtained by the ground camera. We conclude that monitoring goals or research questions that can be answered on a relatively coarse taxonomic level can benefit from an sUAV-based approach because it allows much larger spatial coverage within the time constraints of a low tide interval than is possible by observers on the ground. We demonstrated this large-scale applicability by using sUAV images to develop maps that show the distribution patterns and patchiness of seagrass.

CFD Simulation of a Wing-In-Ground-Effect UAV

NASA Astrophysics Data System (ADS)

Lao, C. T.; Wong, E. T. T.

2018-05-01

This paper reports a numerical analysis on a wing section used for a Wing-In-Ground-Effect (WIG) unmanned aerial vehicle (UAV). The wing geometry was created by SolidWorks and the incompressible Reynolds-averaged Navier-Stokes (RANS) equations were solved with the Spalart–Allmaras turbulence model using CFD software ANSYS FLUENT. In FLUENT, the Spalart-Allmaras model has been implemented to use wall functions when the mesh resolution is not sufficiently fine. This might make it the best choice for relatively crude simulations on coarse meshes where accurate turbulent flow computations are not critical. The results show that the lift coefficient and lift-drag ratio derived excellent performance enhancement by ground effect. However, the moment coefficient shows inconsistency when the wing is operating in very low altitude - this is owing to the difficulty on the stability control of WIG vehicle. A drag polar estimation based on the analysis also indicated that the Oswald (or span) efficiency of the wing was improved by ground effect.

Mission-Oriented Sensor Arrays and UAVs - a Case Study on Environmental Monitoring

NASA Astrophysics Data System (ADS)

Figueira, N. M.; Freire, I. L.; Trindade, O.; Simões, E.

2015-08-01

This paper presents a new concept of UAV mission design in geomatics, applied to the generation of thematic maps for a multitude of civilian and military applications. We discuss the architecture of Mission-Oriented Sensors Arrays (MOSA), proposed in Figueira et Al. (2013), aimed at splitting and decoupling the mission-oriented part of the system (non safety-critical hardware and software) from the aircraft control systems (safety-critical). As a case study, we present an environmental monitoring application for the automatic generation of thematic maps to track gunshot activity in conservation areas. The MOSA modeled for this application integrates information from a thermal camera and an on-the-ground microphone array. The use of microphone arrays technology is of particular interest in this paper. These arrays allow estimation of the direction-of-arrival (DOA) of the incoming sound waves. Information about events of interest is obtained by the fusion of the data provided by the microphone array, captured by the UAV, fused with information from the termal image processing. Preliminary results show the feasibility of the on-the-ground sound processing array and the simulation of the main processing module, to be embedded into an UAV in a future work. The main contributions of this paper are the proposed MOSA system, including concepts, models and architecture.

Determination of Landslide and Driftwood Potentials by Fixed-wing UAV-Borne RGB and NIR images: A Case Study of Shenmu Area in Taiwan

NASA Astrophysics Data System (ADS)

Chen, Su-Chin; Hsiao, Yu-Shen; Chung, Ta-Hsien

2015-04-01

This study is aimed at determining the landslide and driftwood potentials at Shenmu area in Taiwan by Unmanned Aerial Vehicle (UAV). High-resolution orthomosaics and digital surface models (DSMs) are both obtained from several UAV practical surveys by using a red-green-blue(RGB) camera and a near-infrared(NIR) one, respectively. Couples of artificial aerial survey targets are used for ground control in photogrammtry. The algorithm for this study is based on Logistic regression. 8 main factors, which are elevations, terrain slopes, terrain aspects, terrain reliefs, terrain roughness, distances to roads, distances to rivers, land utilizations, are taken into consideration in our Logistic regression model. The related results from UAV are compared with those from traditional photogrammetry. Overall, the study is focusing on monitoring the distribution of the areas with high-risk landslide and driftwood potentials in Shenmu area by Fixed-wing UAV-Borne RGB and NIR images. We also further analyze the relationship between forests, landslides, disaster potentials and upper river areas.

DTM Generation with Uav Based Photogrammetric Point Cloud

NASA Astrophysics Data System (ADS)

Polat, N.; Uysal, M.

2017-11-01

Nowadays Unmanned Aerial Vehicles (UAVs) are widely used in many applications for different purposes. Their benefits however are not entirely detected due to the integration capabilities of other equipment such as; digital camera, GPS, or laser scanner. The main scope of this paper is evaluating performance of cameras integrated UAV for geomatic applications by the way of Digital Terrain Model (DTM) generation in a small area. In this purpose, 7 ground control points are surveyed with RTK and 420 photographs are captured. Over 30 million georeferenced points were used in DTM generation process. Accuracy of the DTM was evaluated with 5 check points. The root mean square error is calculated as 17.1 cm for an altitude of 100 m. Besides, a LiDAR derived DTM is used as reference in order to calculate correlation. The UAV based DTM has o 94.5 % correlation with reference DTM. Outcomes of the study show that it is possible to use the UAV Photogrammetry data as map producing, surveying, and some other engineering applications with the advantages of low-cost, time conservation, and minimum field work.

Towards collaboration between unmanned aerial and ground vehicles for precision agriculture

NASA Astrophysics Data System (ADS)

Bhandari, Subodh; Raheja, Amar; Green, Robert L.; Do, Dat

2017-05-01

This paper presents the work being conducted at Cal Poly Pomona on the collaboration between unmanned aerial and ground vehicles for precision agriculture. The unmanned aerial vehicles (UAVs), equipped with multispectral/hyperspectral cameras and RGB cameras, take images of the crops while flying autonomously. The images are post processed or can be processed onboard. The processed images are used in the detection of unhealthy plants. Aerial data can be used by the UAVs and unmanned ground vehicles (UGVs) for various purposes including care of crops, harvest estimation, etc. The images can also be useful for optimized harvesting by isolating low yielding plants. These vehicles can be operated autonomously with limited or no human intervention, thereby reducing cost and limiting human exposure to agricultural chemicals. The paper discuss the autonomous UAV and UGV platforms used for the research, sensor integration, and experimental testing. Methods for ground truthing the results obtained from the UAVs will be used. The paper will also discuss equipping the UGV with a robotic arm for removing the unhealthy plants and/or weeds.

Assessing UAVs in Monitoring Crop Evapotranspiration within a Heterogeneous Soil

NASA Astrophysics Data System (ADS)

Rouze, G.; Neely, H.; Morgan, C.; Kustas, W. P.; McKee, L.; Prueger, J. H.; Cope, D.; Yang, C.; Thomasson, A.; Jung, J.

2017-12-01

Airborne and satellite remote sensing methods have been developed to provide ET estimates across entire management fields. However, airborne-based ET is not particularly cost-effective and satellite-based ET provides insufficient spatial/temporal information. ET estimations through remote sensing are also problematic where soils are highly variable within a given management field. Unlike airborne/satellite-based ET, Unmanned Aerial Vehicle (UAV)-based ET has the potential to increase the spatial and temporal detail of these measurements, particularly within a heterogeneous soil landscape. However, it is unclear to what extent UAVs can model ET. The overall goal of this project was to assess the capability of UAVs in modeling ET across a heterogeneous landscape. Within a 20-ha irrigated cotton field in Central Texas, low-altitude UAV surveys were conducted throughout the growing season over two soil types. UAVs were equipped with thermal and multispectral cameras to obtain canopy temperature and NDVI, respectively. UAV data were supplemented simultaneously with ground-truth measurements such as Leaf Area Index (LAI) and plant height. Both remote sensing and ground-truth parameters were used to model ET using a Two-Source Energy Balance (TSEB) model. UAV-based estimations of ET and other energy balance components were validated against energy balance measurements obtained from nearby eddy covariance towers that were installed within each soil type. UAV-based ET fluxes were also compared with airborne and satellite (Landsat 8)-based ET fluxes collected near the time of the UAV survey.

Development of an Unmanned Aircraft System and Cyberinfrastructure for Environmental Science Research

NASA Astrophysics Data System (ADS)

Brady, J. J.; Tweedie, C. E.; Escapita, I. J.

2009-12-01

There is a fundamental need to improve capacities for monitoring environmental change using remote sensing technologies. Recently, researchers have begun using Unmanned Aerial Vehicles (UAVs) to expand and improve upon remote sensing capabilities. Limitations to most non-military and relatively small-scale Unmanned Aircraft Systems (UASs) include a need to develop more reliable communications between ground and aircraft, tools to optimize flight control, real time data processing, and visually ascertaining the quantity of data collected while in air. Here we present a prototype software system that has enhanced communication between ground and the vehicle, can synthesize near real time data acquired from sensors on board, can log operation data during flights, and can visually demonstrate the amount and quality of data for a sampling area. This software has the capacity to greatly improve the utilization of UAS in the environmental sciences. The software system is being designed for use on a paraglider UAV that has a suite of sensors suitable for characterizing the footprints of eddy covariance towers situated in the Chihuahuan Desert and in the Arctic. Sensors on board relay operational flight data (airspeed, ground speed, latitude, longitude, pitch, yaw, roll, acceleration, and video) as well as a suite of customized sensors. Additional sensors can be added to an on board laptop or a CR1000 data logger thereby allowing data from these sensors to be visualized in the prototype software. This poster will describe the development, use and customization of our UAS and multimedia will be available during AGU to illustrate the system in use. UAV on workbench in the lab UAV in flight

Enabling UAV Navigation with Sensor and Environmental Uncertainty in Cluttered and GPS-Denied Environments

PubMed Central

Vanegas, Fernando; Gonzalez, Felipe

2016-01-01

Unmanned Aerial Vehicles (UAV) can navigate with low risk in obstacle-free environments using ground control stations that plan a series of GPS waypoints as a path to follow. This GPS waypoint navigation does however become dangerous in environments where the GPS signal is faulty or is only present in some places and when the airspace is filled with obstacles. UAV navigation then becomes challenging because the UAV uses other sensors, which in turn generate uncertainty about its localisation and motion systems, especially if the UAV is a low cost platform. Additional uncertainty affects the mission when the UAV goal location is only partially known and can only be discovered by exploring and detecting a target. This navigation problem is established in this research as a Partially-Observable Markov Decision Process (POMDP), so as to produce a policy that maps a set of motion commands to belief states and observations. The policy is calculated and updated on-line while flying with a newly-developed system for UAV Uncertainty-Based Navigation (UBNAV), to navigate in cluttered and GPS-denied environments using observations and executing motion commands instead of waypoints. Experimental results in both simulation and real flight tests show that the UAV finds a path on-line to a region where it can explore and detect a target without colliding with obstacles. UBNAV provides a new method and an enabling technology for scientists to implement and test UAV navigation missions with uncertainty where targets must be detected using on-line POMDP in real flight scenarios. PMID:27171096

Comprehensive UAV agricultural remote-sensing research at Texas A M University

NASA Astrophysics Data System (ADS)

Thomasson, J. Alex; Shi, Yeyin; Olsenholler, Jeffrey; Valasek, John; Murray, Seth C.; Bishop, Michael P.

2016-05-01

Unmanned aerial vehicles (UAVs) have advantages over manned vehicles for agricultural remote sensing. Flying UAVs is less expensive, is more flexible in scheduling, enables lower altitudes, uses lower speeds, and provides better spatial resolution for imaging. The main disadvantage is that, at lower altitudes and speeds, only small areas can be imaged. However, on large farms with contiguous fields, high-quality images can be collected regularly by using UAVs with appropriate sensing technologies that enable high-quality image mosaics to be created with sufficient metadata and ground-control points. In the United States, rules governing the use of aircraft are promulgated and enforced by the Federal Aviation Administration (FAA), and rules governing UAVs are currently in flux. Operators must apply for appropriate permissions to fly UAVs. In the summer of 2015 Texas A&M University's agricultural research agency, Texas A&M AgriLife Research, embarked on a comprehensive program of remote sensing with UAVs at its 568-ha Brazos Bottom Research Farm. This farm is made up of numerous fields where various crops are grown in plots or complete fields. The crops include cotton, corn, sorghum, and wheat. After gaining FAA permission to fly at the farm, the research team used multiple fixed-wing and rotary-wing UAVs along with various sensors to collect images over all parts of the farm at least once per week. This article reports on details of flight operations and sensing and analysis protocols, and it includes some lessons learned in the process of developing a UAV remote-sensing effort of this sort.

Enabling UAV Navigation with Sensor and Environmental Uncertainty in Cluttered and GPS-Denied Environments.

PubMed

Vanegas, Fernando; Gonzalez, Felipe

2016-05-10

Unmanned Aerial Vehicles (UAV) can navigate with low risk in obstacle-free environments using ground control stations that plan a series of GPS waypoints as a path to follow. This GPS waypoint navigation does however become dangerous in environments where the GPS signal is faulty or is only present in some places and when the airspace is filled with obstacles. UAV navigation then becomes challenging because the UAV uses other sensors, which in turn generate uncertainty about its localisation and motion systems, especially if the UAV is a low cost platform. Additional uncertainty affects the mission when the UAV goal location is only partially known and can only be discovered by exploring and detecting a target. This navigation problem is established in this research as a Partially-Observable Markov Decision Process (POMDP), so as to produce a policy that maps a set of motion commands to belief states and observations. The policy is calculated and updated on-line while flying with a newly-developed system for UAV Uncertainty-Based Navigation (UBNAV), to navigate in cluttered and GPS-denied environments using observations and executing motion commands instead of waypoints. Experimental results in both simulation and real flight tests show that the UAV finds a path on-line to a region where it can explore and detect a target without colliding with obstacles. UBNAV provides a new method and an enabling technology for scientists to implement and test UAV navigation missions with uncertainty where targets must be detected using on-line POMDP in real flight scenarios.

Three-Dimensional Digital Documentation of Heritage Sites Using Terrestrial Laser Scanning and Unmanned Aerial Vehicle Photogrammetry

NASA Astrophysics Data System (ADS)

Jo, Y. H.; Kim, J. Y.

2017-08-01

Three-dimensional digital documentation is an important technique for the maintenance and monitoring of cultural heritage sites. This study focuses on the three-dimensional digital documentation of the Magoksa Temple, Republic of Korea, using a combination of terrestrial laser scanning and unmanned aerial vehicle (UAV) photogrammetry. Terrestrial laser scanning mostly acquired the vertical geometry of the buildings. In addition, the digital orthoimage produced by UAV photogrammetry had higher horizontal data acquisition rate than that produced by terrestrial laser scanning. Thus, the scanning and UAV photogrammetry were merged by matching 20 corresponding points and an absolute coordinate system was established using seven ground control points. The final, complete threedimensional shape had perfect horizontal and vertical geometries. This study demonstrates the potential of integrating terrestrial laser scanning and UAV photogrammetry for three-dimensional digital documentation. This new technique is expected to contribute to the three-dimensional digital documentation and spatial analysis of cultural heritage sites.

Comparing and combining terrestrial laser scanning with ground-and UAV-based imaging for national-level assessment of soil erosion

NASA Astrophysics Data System (ADS)

McShane, Gareth; James, Mike R.; Quinton, John; Anderson, Karen; DeBell, Leon; Evans, Martin; Farrow, Luke; Glendell, Miriam; Jones, Lee; Kirkham, Matthew; Lark, Murray; Rawlins, Barry; Rickson, Jane; Quine, Tim; Wetherelt, Andy; Brazier, Richard

2014-05-01

3D topographic or surface models are increasingly being utilised for a wide range of applications and are established tools in geomorphological research. In this pilot study 'a cost effective framework for monitoring soil erosion in England and Wales', funded by the UK Department for Environment, Food and Rural Affairs (Defra), we compare methods of collecting topographic measurements via remote sensing for detailed studies of dynamic processes such as erosion and mass movement. The techniques assessed are terrestrial laser scanning (TLS), and unmanned aerial vehicle (UAV) photography and ground-based photography, processed using structure-from-motion (SfM) 3D reconstruction software. The methods will be applied in regions of different land use, including arable and horticultural, upland and semi natural habitats, and grassland, to quantify visible erosion pathways at the site scale. Volumetric estimates of soil loss will be quantified using the digital surface models (DSMs) provided by each technique and a modelled pre-erosion surface. Visible erosion and severity will be independently established through each technique, with their results compared and combined effectiveness assessed. A fixed delta-wing UAV (QuestUAV, http://www.questuav.com/) captures photos from a range of altitudes and angles over the study area, with automated SfM-based processing enabling rapid orthophoto production to support ground-based data acquisition. At sites with suitable scale erosion features, UAV data will also provide a DSM for volume loss measurement. Terrestrial laser scanning will provide detailed, accurate, high density measurements of the ground surface over long (100s m) distances. Ground-based photography is anticipated to be most useful for characterising small and difficult to view features. By using a consumer-grade digital camera and an SfM-based approach (using Agisoft Photoscan version 1.0.0, http://www.agisoft.ru/products/photoscan/), less expertise and fewer control measurements are required compared with traditional photogrammetry, and image processing is automated. Differential GPS data will be used to geo-reference the models to facilitate comparison. The relative advantages, limitations and cost-effectiveness of each approach will be established, and which technique, or combination of techniques, is most appropriate to monitor, model and estimate soil erosion at the national scale, determined.

Development of a Near Ground Remote Sensing System

PubMed Central

Zhang, Yanchao; Xiao, Yuzhao; Zhuang, Zaichun; Zhou, Liping; Liu, Fei; He, Yong

2016-01-01

Unmanned Aerial Vehicles (UAVs) have shown great potential in agriculture and are increasingly being developed for agricultural use. There are still a lot of experiments that need to be done to improve their performance and explore new uses, but experiments using UAVs are limited by many conditions like weather and location and the time it takes to prepare for a flight. To promote UAV remote sensing, a near ground remote sensing platform was developed. This platform consists of three major parts: (1) mechanical structures like a horizontal rail, vertical cylinder, and three axes gimbal; (2) power supply and control parts; (3) onboard application components. This platform covers five degrees of freedom (DOFs): horizontal, vertical, pitch, roll, yaw. A stm32 ARM single chip was used as the controller of the whole platform and another stm32 MCU was used to stabilize the gimbal. The gimbal stabilizer communicates with the main controller via a CAN bus. A multispectral camera was mounted on the gimbal. Software written in C++ language was developed as the graphical user interface. Operating parameters were set via this software and the working status was displayed in this software. To test how well the system works, a laser distance meter was used to measure the slide rail’s repeat accuracy. A 3-axis vibration analyzer was used to test the system stability. Test results show that the horizontal repeat accuracy was less than 2 mm; vertical repeat accuracy was less than 1 mm; vibration was less than 2 g and remained at an acceptable level. This system has high accuracy and stability and can therefore be used for various near ground remote sensing studies. PMID:27164111

SUSI 62 A Robust and Safe Parachute Uav with Long Flight Time and Good Payload

NASA Astrophysics Data System (ADS)

Thamm, H. P.

2011-09-01

In many research areas in the geo-sciences (erosion, land use, land cover change, etc.) or applications (e.g. forest management, mining, land management etc.) there is a demand for remote sensing images of a very high spatial and temporal resolution. Due to the high costs of classic aerial photo campaigns, the use of a UAV is a promising option for obtaining the desired remote sensed information at the time it is needed. However, the UAV must be easy to operate, safe, robust and should have a high payload and long flight time. For that purpose, the parachute UAV SUSI 62 was developed. It consists of a steel frame with a powerful 62 cm3 2- stroke engine and a parachute wing. The frame can be easily disassembled for transportation or to replace parts. On the frame there is a gimbal mounted sensor carrier where different sensors, standard SLR cameras and/or multi-spectral and thermal sensors can be mounted. Due to the design of the parachute, the SUSI 62 is very easy to control. Two different parachute sizes are available for different wind speed conditions. The SUSI 62 has a payload of up to 8 kg providing options to use different sensors at the same time or to extend flight duration. The SUSI 62 needs a runway of between 10 m and 50 m, depending on the wind conditions. The maximum flight speed is approximately 50 km/h. It can be operated in a wind speed of up to 6 m/s. The design of the system utilising a parachute UAV makes it comparatively safe as a failure of the electronics or the remote control only results in the UAV coming to the ground at a slow speed. The video signal from the camera, the GPS coordinates and other flight parameters are transmitted to the ground station in real time. An autopilot is available, which guarantees that the area of investigation is covered at the desired resolution and overlap. The robustly designed SUSI 62 has been used successfully in Europe, Africa and Australia for scientific projects and also for agricultural, forestry and industrial applications.

Demonstrating Acquisition of Real-Time Thermal Data Over Fires Utilizing UAVs

NASA Technical Reports Server (NTRS)

Ambrosia, Vincent G.; Wegener, Steven S.; Brass, James A.; Buechel, Sally W.; Peterson, David L. (Technical Monitor)

2002-01-01

A disaster mitigation demonstration, designed to integrate remote-piloted aerial platforms, a thermal infrared imaging payload, over-the-horizon (OTH) data telemetry and advanced image geo-rectification technologies was initiated in 2001. Project FiRE incorporates the use of a remotely piloted Uninhabited Aerial Vehicle (UAV), thermal imagery, and over-the-horizon satellite data telemetry to provide geo-corrected data over a controlled burn, to a fire management community in near real-time. The experiment demonstrated the use of a thermal multi-spectral scanner, integrated on a large payload capacity UAV, distributing data over-the-horizon via satellite communication telemetry equipment, and precision geo-rectification of the resultant data on the ground for data distribution to the Internet. The use of the UAV allowed remote-piloted flight (thereby reducing the potential for loss of human life during hazardous missions), and the ability to "finger and stare" over the fire for extended periods of time (beyond the capabilities of human-pilot endurance). Improved bit-rate capacity telemetry capabilities increased the amount, structure, and information content of the image data relayed to the ground. The integration of precision navigation instrumentation allowed improved accuracies in geo-rectification of the resultant imagery, easing data ingestion and overlay in a GIS framework. We focus on these technological advances and demonstrate how these emerging technologies can be readily integrated to support disaster mitigation and monitoring strategies regionally and nationally.

Migration strategies for service-enabling ground control stations for unmanned systems

NASA Astrophysics Data System (ADS)

Kroculick, Joseph B.

2011-06-01

Future unmanned systems will be integrated into the Global Information Grid (GIG) and support net-centric data sharing, where information in a domain is exposed to a wide variety of GIG stakeholders that can make use of the information provided. Adopting a Service-Oriented Architecture (SOA) approach to package reusable UAV control station functionality into common control services provides a number of benefits including enabling dynamic plug and play of components depending on changing mission requirements, supporting information sharing to the enterprise, and integrating information from authoritative sources such as mission planners with the UAV control stations data model. It also allows the wider enterprise community to use the services provided by unmanned systems and improve data quality to support more effective decision-making. We explore current challenges in migrating UAV control systems that manage multiple types of vehicles to a Service-Oriented Architecture (SOA). Service-oriented analysis involves reviewing legacy systems and determining which components can be made into a service. Existing UAV control stations provide audio/visual, navigation, and vehicle health and status information that are useful to C4I systems. However, many were designed to be closed systems with proprietary software and hardware implementations, message formats, and specific mission requirements. An architecture analysis can be performed that reviews legacy systems and determines which components can be made into a service. A phased SOA adoption approach can then be developed that improves system interoperability.

Confidential and Authenticated Communications in a Large Fixed-Wing UAV Swarm

DTIC Science & Technology

2016-12-01

either a UAV or a ground station. Asymmetric cryptography is not an option for swarm communications. It is a potential option for initially keying or...each UAV grows ten bytes for each UAV in the swarm, and a 30% overhead is added on for worst case cryptography . The resulting throughput is...analysis in Section IV, we can predict the burden that cryptography places on the ODroid computer. Given that the average unencrypted message size was

Conformal Lightweight Antenna Structures for Aeronautical Communication Technologies

NASA Technical Reports Server (NTRS)

Meador, Mary Ann

2017-01-01

This project is to develop antennas which enable beyond line of sight (BLOS) command and control for UAVs. We will take advantage of newly assigned provisional Ku-band spectrum for UAVs and use unique antenna designs to avoid interference with ground systems. This will involve designing antennas with high isotropic effective radiated power (EIRP) and ultra-low sidelobes. The antennas will be made with polymer aerogel as a substrate to both reduce weight and improve performance, as demonstrated in an Aero Seedling. In addition, designing the antennas to be conformal to the aircraft fuselage will reduce drag.

Multi-Agent Cooperative Target Search

PubMed Central

Hu, Jinwen; Xie, Lihua; Xu, Jun; Xu, Zhao

2014-01-01

This paper addresses a vision-based cooperative search for multiple mobile ground targets by a group of unmanned aerial vehicles (UAVs) with limited sensing and communication capabilities. The airborne camera on each UAV has a limited field of view and its target discriminability varies as a function of altitude. First, by dividing the whole surveillance region into cells, a probability map can be formed for each UAV indicating the probability of target existence within each cell. Then, we propose a distributed probability map updating model which includes the fusion of measurement information, information sharing among neighboring agents, information decay and transmission due to environmental changes such as the target movement. Furthermore, we formulate the target search problem as a multi-agent cooperative coverage control problem by optimizing the collective coverage area and the detection performance. The proposed map updating model and the cooperative control scheme are distributed, i.e., assuming that each agent only communicates with its neighbors within its communication range. Finally, the effectiveness of the proposed algorithms is illustrated by simulation. PMID:24865884

Optimising UAV topographic surveys processed with structure-from-motion: Ground control quality, quantity and bundle adjustment

NASA Astrophysics Data System (ADS)

James, Mike R.; Robson, Stuart; d'Oleire-Oltmanns, Sebastian; Niethammer, Uwe

2016-04-01

Structure-from-motion (SfM) algorithms are greatly facilitating the production of detailed topographic models based on images collected by unmanned aerial vehicles (UAVs). However, SfM-based software does not generally provide the rigorous photogrammetric analysis required to fully understand survey quality. Consequently, error related to problems in control point data or the distribution of control points can remain undiscovered. Even if these errors are not large in magnitude, they can be systematic, and thus have strong implications for the use of products such as digital elevation models (DEMs) and orthophotos. Here, we develop a Monte Carlo approach to (1) improve the accuracy of products when SfM-based processing is used and (2) reduce the associated field effort by identifying suitable lower density deployments of ground control points. The method highlights over-parameterisation during camera self-calibration and provides enhanced insight into control point performance when rigorous error metrics are not available. Processing was implemented using commonly-used SfM-based software (Agisoft PhotoScan), which we augment with semi-automated and automated GCPs image measurement. We apply the Monte Carlo method to two contrasting case studies - an erosion gully survey (Taurodont, Morocco) carried out with an fixed-wing UAV, and an active landslide survey (Super-Sauze, France), acquired using a manually controlled quadcopter. The results highlight the differences in the control requirements for the two sites, and we explore the implications for future surveys. We illustrate DEM sensitivity to critical processing parameters and show how the use of appropriate parameter values increases DEM repeatability and reduces the spatial variability of error due to processing artefacts.

Graph theoretic framework based cooperative control and estimation of multiple UAVs for target tracking

NASA Astrophysics Data System (ADS)

Ahmed, Mousumi

Designing the control technique for nonlinear dynamic systems is a significant challenge. Approaches to designing a nonlinear controller are studied and an extensive study on backstepping based technique is performed in this research with the purpose of tracking a moving target autonomously. Our main motivation is to explore the controller for cooperative and coordinating unmanned vehicles in a target tracking application. To start with, a general theoretical framework for target tracking is studied and a controller in three dimensional environment for a single UAV is designed. This research is primarily focused on finding a generalized method which can be applied to track almost any reference trajectory. The backstepping technique is employed to derive the controller for a simplified UAV kinematic model. This controller can compute three autopilot modes i.e. velocity, ground heading (or course angle), and flight path angle for tracking the unmanned vehicle. Numerical implementation is performed in MATLAB with the assumption of having perfect and full state information of the target to investigate the accuracy of the proposed controller. This controller is then frozen for the multi-vehicle problem. Distributed or decentralized cooperative control is discussed in the context of multi-agent systems. A consensus based cooperative control is studied; such consensus based control problem can be viewed from the algebraic graph theory concepts. The communication structure between the UAVs is represented by the dynamic graph where UAVs are represented by the nodes and the communication links are represented by the edges. The previously designed controller is augmented to account for the group to obtain consensus based on their communication. A theoretical development of the controller for the cooperative group of UAVs is presented and the simulation results for different communication topologies are shown. This research also investigates the cases where the communication topology switches to a different topology over particular time instants. Lyapunov analysis is performed to show stability in all cases. Another important aspect of this dissertation research is to implement the controller for the case, where perfect or full state information is not available. This necessitates the design of an estimator to estimate the system state. A nonlinear estimator, Extended Kalman Filter (EKF) is first developed for target tracking with a single UAV. The uncertainties involved with the measurement model and dynamics model are considered as zero mean Gaussian noises with some known covariances. The measurements of the full state of the target are not available and only the range, elevation, and azimuth angle are available from an onboard seeker sensor. A separate EKF is designed to estimate the UAV's own state where the state measurement is available through on-board sensors. The controller computes the three control commands based on the estimated states of target and its own states. Estimation based control laws is also implemented for colored noise measurement uncertainties, and the controller performance is shown with the simulation results. The estimation based control approach is then extended for the cooperative target tracking case. The target information is available to the network and a separate estimator is used to estimate target states. All of the UAVs in the network apply the same control law and the only difference is that each UAV updates the commands according to their connection. The simulation is performed for both cases of fixed and time varying communication topology. Monte Carlo simulation is also performed with different sample noises to investigate the performance of the estimator. The proposed technique is shown to be simple and robust to noisy environments.

Possibilities of Uas for Maritime Monitoring

NASA Astrophysics Data System (ADS)

Klimkowska, A.; Lee, I.; Choi, K.

2016-06-01

In the last few years, Unmanned Aircraft Systems (UAS) have become more important and its use for different application is appreciated. At the beginning UAS were used for military purposes. These successful applications initiated interest among researchers to find uses of UAS for civilian purposes, as they are alternative to both manned and satellite systems in acquiring high-resolution remote sensing data at lower cost while long flight duration. As UAS are built from many components such as unmanned aerial vehicle (UAV), sensing payloads, communication systems, ground control stations, recovery and launch equipment, and supporting equipment, knowledge about its functionality and characteristics is crucial for missions. Therefore, finding appropriate configuration of all elements to fulfill requirements of the mission is a very difficult, yet important task. UAS may be used in various maritime applications such as ship detection, red tide detection and monitoring, border patrol, tracking of pollution at sea and hurricane monitoring just to mention few. One of the greatest advantages of UAV is their ability to fly over dangerous and hazardous areas, where sending manned aircraft could be risky for a crew. In this article brief description of aerial unmanned system components is introduced. Firstly characteristics of unmanned aerial vehicles are presented, it continues with introducing inertial navigation system, communication systems, sensing payloads, ground control stations, and ground and recovery equipment. Next part introduces some examples of UAS for maritime applications. This is followed by suggestions of key indicators which should be taken into consideration while choosing UAS. Last part talks about configuration schemes of UAVs and sensor payloads suggested for some maritime applications.

A performance study of unmanned aerial vehicle-based sensor networks under cyber attack

NASA Astrophysics Data System (ADS)

Puchaty, Ethan M.

In UAV-based sensor networks, an emerging area of interest is the performance of these networks under cyber attack. This study seeks to evaluate the performance trade-offs from a System-of-Systems (SoS) perspective between various UAV communications architecture options in the context two missions: tracking ballistic missiles and tracking insurgents. An agent-based discrete event simulation is used to model a sensor communication network consisting of UAVs, military communications satellites, ground relay stations, and a mission control center. Network susceptibility to cyber attack is modeled with probabilistic failures and induced data variability, with performance metrics focusing on information availability, latency, and trustworthiness. Results demonstrated that using UAVs as routers increased network availability with a minimal latency penalty and communications satellite networks were best for long distance operations. Redundancy in the number of links between communication nodes helped mitigate cyber-caused link failures and add robustness in cases of induced data variability by an adversary. However, when failures were not independent, redundancy and UAV routing were detrimental in some cases to network performance. Sensitivity studies indicated that long cyber-caused downtimes and increasing failure dependencies resulted in build-ups of failures and caused significant degradations in network performance.

Seasonal associations and atmospheric transport distances of Fusarium collected with unmanned aerial vehicles and ground-based sampling devices

NASA Astrophysics Data System (ADS)

Schmale, David; Ross, Shane; Lin, Binbin

2014-05-01

Spores of fungi in the genus Fusarium may be transported through the atmosphere over long distances. Members of this genus are important pathogens and mycotoxin producers. New information is needed to characterize seasonal trends in atmospheric loads of Fusarium and to pinpoint the source(s) of inoculum at both local (farm) and regional (state or country) scales. Spores of Fusarium were collected from the atmosphere in an agricultural ecosystem in Blacksburg, VA, USA using a Burkard volumetric sampler (BVS) 1 m above ground level and autonomous unmanned aerial vehicles (UAVs) 100 m above ground level. More than 2,200 colony forming units (CFUs) of Fusarium were collected during 104 BVS sampling periods and 180 UAV sampling periods over four calendar years (2009-2012). Spore concentrations ranged from 0 to 13 and 0 to 23 spores m-3 for the BVS and the UAVs, respectively. Spore concentrations were generally higher in the fall, spring, and summer, and lower in the winter. Spore concentrations from the BVS were generally higher than those from the UAVs for both seasonal and hourly collections. Some of the species of Fusarium identified from our collections have not been previously reported in the state of Virginia. A Gaussian plume transport model was used to estimate distances to the potential inoculum source(s) by season. This work extends previous studies showing an association between atmospheric transport barriers (Lagrangian coherent structures or LCSs) and the movement of Fusarium in the lower atmosphere. An increased understanding of the aerobiology of Fusarium may contribute to new and improved control strategies for diseases causes by fusaria in the future.

A Novel Methodology for Improving Plant Pest Surveillance in Vineyards and Crops Using UAV-Based Hyperspectral and Spatial Data.

PubMed

Vanegas, Fernando; Bratanov, Dmitry; Powell, Kevin; Weiss, John; Gonzalez, Felipe

2018-01-17

Recent advances in remote sensed imagery and geospatial image processing using unmanned aerial vehicles (UAVs) have enabled the rapid and ongoing development of monitoring tools for crop management and the detection/surveillance of insect pests. This paper describes a (UAV) remote sensing-based methodology to increase the efficiency of existing surveillance practices (human inspectors and insect traps) for detecting pest infestations (e.g., grape phylloxera in vineyards). The methodology uses a UAV integrated with advanced digital hyperspectral, multispectral, and RGB sensors. We implemented the methodology for the development of a predictive model for phylloxera detection. In this method, we explore the combination of airborne RGB, multispectral, and hyperspectral imagery with ground-based data at two separate time periods and under different levels of phylloxera infestation. We describe the technology used-the sensors, the UAV, and the flight operations-the processing workflow of the datasets from each imagery type, and the methods for combining multiple airborne with ground-based datasets. Finally, we present relevant results of correlation between the different processed datasets. The objective of this research is to develop a novel methodology for collecting, processing, analising and integrating multispectral, hyperspectral, ground and spatial data to remote sense different variables in different applications, such as, in this case, plant pest surveillance. The development of such methodology would provide researchers, agronomists, and UAV practitioners reliable data collection protocols and methods to achieve faster processing techniques and integrate multiple sources of data in diverse remote sensing applications.

Consensus-based distributed estimation in multi-agent systems with time delay

NASA Astrophysics Data System (ADS)

Abdelmawgoud, Ahmed

During the last years, research in the field of cooperative control of swarm of robots, especially Unmanned Aerial Vehicles (UAV); have been improved due to the increase of UAV applications. The ability to track targets using UAVs has a wide range of applications not only civilian but also military as well. For civilian applications, UAVs can perform tasks including, but not limited to: map an unknown area, weather forecasting, land survey, and search and rescue missions. On the other hand, for military personnel, UAV can track and locate a variety of objects, including the movement of enemy vehicles. Consensus problems arise in a number of applications including coordination of UAVs, information processing in wireless sensor networks, and distributed multi-agent optimization. We consider a widely studied consensus algorithms for processing sensed data by different sensors in wireless sensor networks of dynamic agents. Every agent involved in the network forms a weighted average of its own estimated value of some state with the values received from its neighboring agents. We introduced a novelty of consensus-based distributed estimation algorithms. We propose a new algorithm to reach a consensus given time delay constraints. The proposed algorithm performance was observed in a scenario where a swarm of UAVs measuring the location of a ground maneuvering target. We assume that each UAV computes its state prediction and shares it with its neighbors only. However, the shared information applied to different agents with variant time delays. The entire group of UAVs must reach a consensus on target state. Different scenarios were also simulated to examine the effectiveness and performance in terms of overall estimation error, disagreement between delayed and non-delayed agents, and time to reach a consensus for each parameter contributing on the proposed algorithm.

Small UAV Automatic Ground Collision Avoidance System Design Considerations and Flight Test Results

NASA Technical Reports Server (NTRS)

Sorokowski, Paul; Skoog, Mark; Burrows, Scott; Thomas, SaraKatie

2015-01-01

The National Aeronautics and Space Administration (NASA) Armstrong Flight Research Center Small Unmanned Aerial Vehicle (SUAV) Automatic Ground Collision Avoidance System (Auto GCAS) project demonstrated several important collision avoidance technologies. First, the SUAV Auto GCAS design included capabilities to take advantage of terrain avoidance maneuvers flying turns to either side as well as straight over terrain. Second, the design also included innovative digital elevation model (DEM) scanning methods. The combination of multi-trajectory options and new scanning methods demonstrated the ability to reduce the nuisance potential of the SUAV while maintaining robust terrain avoidance. Third, the Auto GCAS algorithms were hosted on the processor inside a smartphone, providing a lightweight hardware configuration for use in either the ground control station or on board the test aircraft. Finally, compression of DEM data for the entire Earth and successful hosting of that data on the smartphone was demonstrated. The SUAV Auto GCAS project demonstrated that together these methods and technologies have the potential to dramatically reduce the number of controlled flight into terrain mishaps across a wide range of aviation platforms with similar capabilities including UAVs, general aviation aircraft, helicopters, and model aircraft.

Distributed Pheromone-Based Swarming Control of Unmanned Air and Ground Vehicles for RSTA

DTIC Science & Technology

2008-03-20

Forthcoming in Proceedings of SPIE Defense & Security Conference, March 2008, Orlando, FL Distributed Pheromone -Based Swarming Control of Unmanned...describes recent advances in a fully distributed digital pheromone algorithm that has demonstrated its effectiveness in managing the complexity of...onboard digital pheromone responding to the needs of the automatic target recognition algorithms. UAVs and UGVs controlled by the same pheromone algorithm

Unmanned Aerial Vehicle (UAV) Dynamic-Tracking Directional Wireless Antennas for Low Powered Applications that Require Reliable Extended Range Operations in Time Critical Scenarios

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scott G. Bauer; Matthew O. Anderson; James R. Hanneman

2005-10-01

The proven value of DOD Unmanned Aerial Vehicles (UAVs) will ultimately transition to National and Homeland Security missions that require real-time aerial surveillance, situation awareness, force protection, and sensor placement. Public services first responders who routinely risk personal safety to assess and report a situation for emergency actions will likely be the first to benefit from these new unmanned technologies. ‘Packable’ or ‘Portable’ small class UAVs will be particularly useful to the first responder. They require the least amount of training, no fixed infrastructure, and are capable of being launched and recovered from the point of emergency. All UAVs requiremore » wireless communication technologies for real- time applications. Typically on a small UAV, a low bandwidth telemetry link is required for command and control (C2), and systems health monitoring. If the UAV is equipped with a real-time Electro-Optical or Infrared (EO/Ir) video camera payload, a dedicated high bandwidth analog/digital link is usually required for reliable high-resolution imagery. In most cases, both the wireless telemetry and real-time video links will be integrated into the UAV with unity gain omni-directional antennas. With limited on-board power and payload capacity, a small UAV will be limited with the amount of radio-frequency (RF) energy it transmits to the users. Therefore, ‘packable’ and ‘portable’ UAVs will have limited useful operational ranges for first responders. This paper will discuss the limitations of small UAV wireless communications. The discussion will present an approach of utilizing a dynamic ground based real-time tracking high gain directional antenna to provide extend range stand-off operation, potential RF channel reuse, and assured telemetry and data communications from low-powered UAV deployed wireless assets.« less

UAV-based photogrammetry combination of the elevational outcrop and digital surface models: an example of Sanyi active fault in western Taiwan

NASA Astrophysics Data System (ADS)

Hsieh, Cheng-En; Huang, Wen-Jeng; Chang, Ping-Yu; Lo, Wei

2016-04-01

An unmanned aerial vehicle (UAV) with a digital camera is an efficient tool for geologists to investigate structure patterns in the field. By setting ground control points (GCPs), UAV-based photogrammetry provides high-quality and quantitative results such as a digital surface model (DSM) and orthomosaic and elevational images. We combine the elevational outcrop 3D model and a digital surface model together to analyze the structural characteristics of Sanyi active fault in Houli-Fengyuan area, western Taiwan. Furthermore, we collect resistivity survey profiles and drilling core data in the Fengyuan District in order to build the subsurface fault geometry. The ground sample distance (GSD) of an elevational outcrop 3D model is 3.64 cm/pixel in this study. Our preliminary result shows that 5 fault branches are distributed 500 meters wide on the elevational outcrop and the width of Sanyi fault zone is likely much great than this value. Together with our field observations, we propose a structural evolution model to demonstrate how the 5 fault branches developed. The resistivity survey profiles show that Holocene gravel was disturbed by the Sanyi fault in Fengyuan area.

Comparative UAV and Field Phenotyping to Assess Yield and Nitrogen Use Efficiency in Hybrid and Conventional Barley.

PubMed

Kefauver, Shawn C; Vicente, Rubén; Vergara-Díaz, Omar; Fernandez-Gallego, Jose A; Kerfal, Samir; Lopez, Antonio; Melichar, James P E; Serret Molins, María D; Araus, José L

2017-01-01

With the commercialization and increasing availability of Unmanned Aerial Vehicles (UAVs) multiple rotor copters have expanded rapidly in plant phenotyping studies with their ability to provide clear, high resolution images. As such, the traditional bottleneck of plant phenotyping has shifted from data collection to data processing. Fortunately, the necessarily controlled and repetitive design of plant phenotyping allows for the development of semi-automatic computer processing tools that may sufficiently reduce the time spent in data extraction. Here we present a comparison of UAV and field based high throughput plant phenotyping (HTPP) using the free, open-source image analysis software FIJI (Fiji is just ImageJ) using RGB (conventional digital cameras), multispectral and thermal aerial imagery in combination with a matching suite of ground sensors in a study of two hybrids and one conventional barely variety with ten different nitrogen treatments, combining different fertilization levels and application schedules. A detailed correlation network for physiological traits and exploration of the data comparing between treatments and varieties provided insights into crop performance under different management scenarios. Multivariate regression models explained 77.8, 71.6, and 82.7% of the variance in yield from aerial, ground, and combined data sets, respectively.

Vision-Based Target Finding and Inspection of a Ground Target Using a Multirotor UAV System.

PubMed

Hinas, Ajmal; Roberts, Jonathan M; Gonzalez, Felipe

2017-12-17

In this paper, a system that uses an algorithm for target detection and navigation and a multirotor Unmanned Aerial Vehicle (UAV) for finding a ground target and inspecting it closely is presented. The system can also be used for accurate and safe delivery of payloads or spot spraying applications in site-specific crop management. A downward-looking camera attached to a multirotor is used to find the target on the ground. The UAV descends to the target and hovers above the target for a few seconds to inspect the target. A high-level decision algorithm based on an OODA (observe, orient, decide, and act) loop was developed as a solution to address the problem. Navigation of the UAV was achieved by continuously sending local position messages to the autopilot via Mavros. The proposed system performed hovering above the target in three different stages: locate, descend, and hover. The system was tested in multiple trials, in simulations and outdoor tests, from heights of 10 m to 40 m. Results show that the system is highly reliable and robust to sensor errors, drift, and external disturbance.

The Effectiveness of Drone Strikes in Counterinsurgency and Counterterrorism Campaigns

DTIC Science & Technology

2013-09-01

accurate missiles that have the ca- pacity to target individuals, automobiles , and sections of structures such as rooms in a large house. Perhaps the...unmanned aerial ve- hicles (UAVs) or remotely piloted aircraft (RPAs)—are pilotless aircraft controlled by individuals located on the ground, often some...with many of the advantages that ground forces offer in counterinsurgency operations. The fact that drones are pilotless means that their use does

Flight Testing the X-48B at the Dryden Flight Research Center

NASA Technical Reports Server (NTRS)

Cosenito, Gary B.

2010-01-01

Topics discussed include: a) UAV s at NASA Dryden, Past and Present; b) Why Do We Flight Test?; c) The Blended (or Hybrid) Wing-Body Advantage; d) Program Objectives; e) The X-48B Vehicle and Ground Control Station; and f) Flight Test Highlights & Video.

Medium Altitude Endurance Unmanned Air Vehicle

NASA Astrophysics Data System (ADS)

Ernst, Larry L.

1994-10-01

The medium altitude endurance unmanned air vehicle (MAE UAV) program (formerly the tactical endurance TE UAV) is a new effort initiated by the Department of Defense to develop a ground launched UAV that can fly out 500 miles, remain on station for 24 hours, and return. It will transmit high resolution optical, infrared, and synthetic aperture radar (SAR) images of well-defended target areas through satellite links. It will provide near-real-time, releasable, low cost/low risk surveillance, targeting and damage assessment complementary to that of satellites and manned aircraft. The paper describes specific objectives of the MAE UAV program (deliverables and schedule) and the program's unique position as one of several programs to streamline the acquisition process under the cognizance of the newly established Airborne Reconnaissance Office. I discuss the system requirements and operational concept and describe the technical capabilities and characteristics of the major subsystems (airframe, propulsion, navigation, sensors, communication links, ground station, etc.) in some detail.

Efficient structure from motion for oblique UAV images based on maximal spanning tree expansion

NASA Astrophysics Data System (ADS)

Jiang, San; Jiang, Wanshou

2017-10-01

The primary contribution of this paper is an efficient Structure from Motion (SfM) solution for oblique unmanned aerial vehicle (UAV) images. First, an algorithm, considering spatial relationship constraints between image footprints, is designed for match pair selection with the assistance of UAV flight control data and oblique camera mounting angles. Second, a topological connection network (TCN), represented by an undirected weighted graph, is constructed from initial match pairs, which encodes the overlap areas and intersection angles into edge weights. Then, an algorithm, termed MST-Expansion, is proposed to extract the match graph from the TCN, where the TCN is first simplified by a maximum spanning tree (MST). By further analysis of the local structure in the MST, expansion operations are performed on the vertices of the MST for match graph enhancement, which is achieved by introducing critical connections in the expansion directions. Finally, guided by the match graph, an efficient SfM is proposed. Under extensive analysis and comparison, its performance is verified by using three oblique UAV datasets captured with different multi-camera systems. Experimental results demonstrate that the efficiency of image matching is improved, with speedup ratios ranging from 19 to 35, and competitive orientation accuracy is achieved from both relative bundle adjustment (BA) without GCPs (Ground Control Points) and absolute BA with GCPs. At the same time, images in the three datasets are successfully oriented. For the orientation of oblique UAV images, the proposed method can be a more efficient solution.

Method for the visualization of landform by mapping using low altitude UAV application

NASA Astrophysics Data System (ADS)

Sharan Kumar, N.; Ashraf Mohamad Ismail, Mohd; Sukor, Nur Sabahiah Abdul; Cheang, William

2018-05-01

Unmanned Aerial Vehicle (UAV) and Digital Photogrammetry are evolving drastically in mapping technology. The significance and necessity for digital landform mapping are developing with years. In this study, a mapping workflow is applied to obtain two different input data sets which are the orthophoto and DSM. A fine flying technology is used to capture Low Altitude Aerial Photography (LAAP). Low altitude UAV (Drone) with the fixed advanced camera was utilized for imagery while computerized photogrammetry handling using Photo Scan was applied for cartographic information accumulation. The data processing through photogrammetry and orthomosaic processes is the main applications. High imagery quality is essential for the effectiveness and nature of normal mapping output such as 3D model, Digital Elevation Model (DEM), Digital Surface Model (DSM) and Ortho Images. The exactitude of Ground Control Points (GCP), flight altitude and the resolution of the camera are essential for good quality DEM and Orthophoto.

A Novel Methodology for Improving Plant Pest Surveillance in Vineyards and Crops Using UAV-Based Hyperspectral and Spatial Data

PubMed Central

Vanegas, Fernando; Weiss, John; Gonzalez, Felipe

2018-01-01

Recent advances in remote sensed imagery and geospatial image processing using unmanned aerial vehicles (UAVs) have enabled the rapid and ongoing development of monitoring tools for crop management and the detection/surveillance of insect pests. This paper describes a (UAV) remote sensing-based methodology to increase the efficiency of existing surveillance practices (human inspectors and insect traps) for detecting pest infestations (e.g., grape phylloxera in vineyards). The methodology uses a UAV integrated with advanced digital hyperspectral, multispectral, and RGB sensors. We implemented the methodology for the development of a predictive model for phylloxera detection. In this method, we explore the combination of airborne RGB, multispectral, and hyperspectral imagery with ground-based data at two separate time periods and under different levels of phylloxera infestation. We describe the technology used—the sensors, the UAV, and the flight operations—the processing workflow of the datasets from each imagery type, and the methods for combining multiple airborne with ground-based datasets. Finally, we present relevant results of correlation between the different processed datasets. The objective of this research is to develop a novel methodology for collecting, processing, analysing and integrating multispectral, hyperspectral, ground and spatial data to remote sense different variables in different applications, such as, in this case, plant pest surveillance. The development of such methodology would provide researchers, agronomists, and UAV practitioners reliable data collection protocols and methods to achieve faster processing techniques and integrate multiple sources of data in diverse remote sensing applications. PMID:29342101

Vertical and Horizontal Measurements of Ambient Ozone over a Gas and Oil Production Area using a UAV Platform

NASA Astrophysics Data System (ADS)

Jensen, A.; Gowing, I.; Martin, R. S.

2013-12-01

During the 2013 wintertime Uintah Basin Ozone Study (UBOS13), an autonomous unmanned aerial vehicle (UAV) platform, coupled with an on-board UV ozone monitor, flew several spatial profiles near the location (Horse Pool) of other concentrated measurements by other co-investigators. The airframe, part of the Utah Water Research Laboratory's (UWRL) AggieAir UAV program, consisted of a custom-built, battery-operated plane with and 2.4 m (8 ft) wing span and a 12.7 cm x 12.7 cm x 30.5 cm payload bay with a carrying capacity of approximately 2.0 kg. With the current power system, the fully-loaded AggieAir UAV can fly for approximately 45 minutes at a nominal airspeed of 13.4 m/s (30 mph). The system can be operated either in manual control or be flown autonomously following preprogrammed waypoints via a built in GPS system. The AggieAir UAV systems were primarily designed for photographic and telemetry tracking projects. For the UBOS13 flights, a 2B Technologies Model 205 Ozone (O3) monitor was modified for minimal weight optimization, wrapped with lightweight insulation and secured into the UAV payload bay. Additionally, HOBO Model H08-001-02 shielded temperature/datalogger was secured to the exterior of the UAV from parallel thermal profile determination. During the study period, three demonstration flight profiles were obtained on February 17 and 18, 2013: two vertical 'curtain' profiles and a pair of 'stacked' horizontal profiles. As recorded by numerous ground-based monitoring sites, the ozone during the UAV test periods was characterized by initial trends of daytime O3 maximums over 130 ppb, followed by a meteorological front partially ventilating the Basin on the evening of Feb. 17th leading to decreased O3 minimums around 40 ppb. However, the ground level O3 rebuilt quickly to ground level maximums approaching 100 ppb. The vertical 'curtain' flown on the evening of Feb. 17th only reached a maximum elevation of about 2160 m ASL (600 m AGL) due to encountering upper level excessive winds as the low pressure front approached. However the flight was still able to capture a temperature profile indicating a well-mixed atmosphere below about 300 m AGL, sealed by a definitive inversion layer extending to the top of the measurement profile. The measured O3 profile went from about 140 ppb near the ground to around 60 ppb at the start of the inversion layer, and then remained essentially constant until the top of the elevation profile. The vertical profile late in the morning of the following day (after the front had passed), showed nearly straight vertical profiles of temperature (≈2°C) and ozone (35-50 ppb) up to approximately 2400 m ASL (820 m AGL). The stacked horizontal profiles (1650 and 1750 m ASL) flown immediately after the vertical flight of Feb. 17th showed some differences on the horizontal scale, but it was unclear if these differences were associated with terrain differences (topography dropped rapidly to the south) or locational differences in precursor sources. The UAV measured ozone compared favorably to nearby co-investigators (NOAA/ESRL CSD TOPAZ Lidar and CU/INSTAAR tethered balloon).

A UAV System for Observing Volcanoes and Natural Hazards

NASA Astrophysics Data System (ADS)

Saggiani, G.; Persiani, F.; Ceruti, A.; Tortora, P.; Troiani, E.; Giuletti, F.; Amici, S.; Buongiorno, M.; Distefano, G.; Bentini, G.; Bianconi, M.; Cerutti, A.; Nubile, A.; Sugliani, S.; Chiarini, M.; Pennestri, G.; Petrini, S.; Pieri, D.

2007-12-01

Fixed or rotary wing manned aircraft are currently the most commonly used platforms for airborne reconnaissance in response to natural hazards, such as volcanic eruptions, oil spills, wild fires, earthquakes. Such flights are very often undertaken in hazardous flying conditions (e.g., turbulence, downdrafts, reduced visibility, close proximity to dangerous terrain) and can be expensive. To mitigate these two fundamental issues-- safety and cost--we are exploring the use of small (less than 100kg), relatively inexpensive, but effective, unmanned aerial vehicles (UAVs) for this purpose. As an operational test, in 2004 we flew a small autonomous UAV in the airspace above and around Stromboli Volcano. Based in part on this experience, we are adapting the RAVEN UAV system for such natural hazard surveillance missions. RAVEN has a 50km range, with a 3.5m wingspan, main fuselage length of 4.60m, and maximum weight of 56kg. It has autonomous flight capability and a ground control Station for the mission planning and control. It will carry a variety of imaging devices, including a visible camera, and an IR camera. It will also carry an experimental Fourier micro-interferometer based on MOEMS technology, (developed by IMM Institute of CNR), to detect atmospheric trace gases. Such flexible, capable, and easy-to-deploy UAV systems may significantly shorten the time necessary to characterize the nature and scale of the natural hazard threats if used from the outset of, and systematically during, natural hazard events. When appropriately utilized, such UAVs can provide a powerful new hazard mitigation and documentation tool for civil protection hazard responders. This research was carried out under the auspices of the Italian government, and, in part, under contract to NASA at the Jet Propulsion Laboratory.

Unmanned Aerial Vehicles (UAVs): a new tool in counterterrorism operations?

NASA Astrophysics Data System (ADS)

Dörtbudak, Mehmet F.

2015-05-01

Terrorism is not a new phenomenon to the world, yet it remains difficult to define and counter. Countering terrorism requires several measures that must be taken simultaneously; however, counterterrorism strategies of many countries mostly depend on military measures. In the aftermath of the 2001 terrorist attack on the Twin Towers of the World Trade Center, the United States (U.S.) has started and led the campaign of Global War on Terrorism. They have invaded Afghanistan and Iraq and have encountered insurgencies run by terrorist organizations, such as al-Qaeda and its affiliates. The U.S. made the utilization of Air and Space Power very intensively during these operations. In order to implement operations; Intelligence, Surveillance, and Reconnaissance (ISR) assets were used to collect the necessary information. Before the successful insertion of a small number of U.S. Special Operation Force (SOF) teams into Afghanistan, the U.S. Air Force attacked al-Qaeda and Taliban's targets such as infrastructure, airfields, ground forces, command-control facilities etc. As soon as the U.S. troops got on the ground and started to marshal to Kabul, the Air Force supported them by attacking jointly determined targets. The Air Force continued to carry out the missions and played a significant role to achieve the objective of operation during all the time. This is not the only example of utilization of Air and Space Power in counterterrorism and counterinsurgency operations. All around the world, many countries have also made the utilization of Air Power in different missions ranging from ISR to attacking. Thinking that terrorism has a psychological dimension and losing a pilot during operations may result in decreasing the population support to operations, Unmanned Aerial Vehicles (UAVs) started to be used by practitioners and took priority over other assets. Although UAVs have been on the theatre for a long time used for ISR mission in conventional conflicts, with the advent of drones, UAVs have also started to be used for attack missions in counterterrorism operations. In this study, it is aimed to determine whether UAVs are appropriate assets that can be used in counterterrorism operations. The study starts by examining the term terrorism and counterterrorism and discusses the role of the Air and Space Power in counterterrorism operations. After proposing that UAVs are appropriate assets for counterterrorism operations, it continues by explaining types and common usage concepts of UAVs. The advantages and disadvantages of UAVs are put forward from the counterterrorism operations' perspectives. It finally examines the utilization of UAVs in counterterrorism operations. In this context, as much as obtained from open sources, countries' roadmaps, usage concepts, experience, and current structure are examined to determine whether UAVs are appropriate assets in counterterrorism operations. When the advantages of UAVs and the disadvantages of manned systems are analyzed, other findings of our survey will show us that UAVs will be increasingly used in counterterrorism operations

Integration of UAV and ground-based Structure from Motion with Multi-View Stereo photogrammetry and hydrological data to quantify hillslope gully erosion processes in tropical savanna

NASA Astrophysics Data System (ADS)

Koci, J.; Jarihani, B.; Sidle, R. C.; Wilkinson, S. N.; Bartley, R.

2017-12-01

Structure from Motion with Multi-View Stereo (SfM-MVS) photogrammetry provides a cost-effective method of rapidly acquiring high resolution (sub-meter) topographic data, but is rarely used in hydrogeomorphic investigations of gully erosion. This study integrates high resolution topographic and land cover data derived from an unmanned aerial vehicle (UAV) and ground-based SfM-MVS photogrammetry, with rainfall and gully discharge data, to elucidate hydrogeomorphic processes driving hillslope gully erosion. The study is located within a small (13 km2) dry-tropical savanna catchment within the Burdekin River Basin, northeast Australia, which is a major contributor sediments and nutrients to the Great Barrier Reef World Heritage Area. A pre-wet season UAV survey covered an entire hillslope gully system (0.715 km2), and is used to derive topography, ground cover and hydrological flow pathways in the gully contributing area. Ground-based surveys of a single active gully (650 m2) within the broader hillslope are compared between pre- and post-wet season conditions to quantify gully geomorphic change. Rainfall, recorded near to the head of the gully, is related to gully discharge during sporadic storm events. The study provides valuable insights into the relationships among hydrological flow pathways, ground cover, rainfall and runoff, and spatial patterns of gully morphologic change. We demonstrate how UAV and ground-based SfM-MVS photogrammetry can be used to improve hydrogeomorphic process understanding and aid in the modelling and management of hillslope gully systems.

Scalable autonomous operations of unmanned assets

NASA Astrophysics Data System (ADS)

Jung, Sunghun

Although there have been great theoretical advances in the region of Unmanned Aerial Vehicle (UAV) autonomy, applications of those theories into real world are still hesitated due to unexpected disturbances. Most of UAVs which are currently used are mainly, strictly speaking, Remotely Piloted Vehicles (RPA) since most works related with the flight control, sensor data analysis, and decision makings are done by human operators. To increase the degree of autonomy, many researches are focused on developing Unmanned Autonomous Aerial Vehicle (UAAV) which can takeoff, fly to the interested area by avoiding unexpected obstacles, perform various missions with decision makings, come back to the base station, and land on by itself without any human operators. To improve the performance of UAVs, the accuracies of position and orientation sensors are enhanced by integrating a Unmanned Ground Vehicle (UGV) or a solar compass to a UAV; Position sensor accuracy of a GPS sensor on a UAV is improved by referencing the position of a UGV which is calculated by using three GPS sensors and Weighted Centroid Localization (WCL) method; Orientation sensor accuracy is improved as well by using Three Pixel Theorem (TPT) and integrating a solar compass which composed of nine light sensors to a magnetic compass. Also, improved health management of a UAV is fulfilled by developing a wireless autonomous charging station which uses four pairs of transmitter and receiver magnetic loops with four robotic arms. For the software aspect, I also analyze the error propagation of the proposed mission planning hierarchy to achieve the safest size of the buffer zone. In addition, among seven future research areas regarding UAV, this paper mainly focuses on developing algorithms of path planning, trajectory generation, and cooperative tactics for the operations of multiple UAVs using GA based multiple Traveling Salesman Problem (mTSP) which is solved by dividing into m number of Traveling Salesman Problems (TSP) using two region division methods such as Uniform Region Division (URD) and K-means Voronoi Region Division (KVRD). The topic of the maximum fuel efficiency is also dealt to ensure the minimum amount fuel consumption to perform surveillance on a given region using multiple UAVs. Last but not least, I present an application example of cattle roundup with two UAVs and two animals using the feedback linearization controller.

Unmanned aerial vehicles (UAVs) for surveying marine fauna: a dugong case study.

PubMed

Hodgson, Amanda; Kelly, Natalie; Peel, David

2013-01-01

Aerial surveys of marine mammals are routinely conducted to assess and monitor species' habitat use and population status. In Australia, dugongs (Dugong dugon) are regularly surveyed and long-term datasets have formed the basis for defining habitat of high conservation value and risk assessments of human impacts. Unmanned aerial vehicles (UAVs) may facilitate more accurate, human-risk free, and cheaper aerial surveys. We undertook the first Australian UAV survey trial in Shark Bay, western Australia. We conducted seven flights of the ScanEagle UAV, mounted with a digital SLR camera payload. During each flight, ten transects covering a 1.3 km(2) area frequently used by dugongs, were flown at 500, 750 and 1000 ft. Image (photograph) capture was controlled via the Ground Control Station and the capture rate was scheduled to achieve a prescribed 10% overlap between images along transect lines. Images were manually reviewed post hoc for animals and scored according to sun glitter, Beaufort Sea state and turbidity. We captured 6243 images, 627 containing dugongs. We also identified whales, dolphins, turtles and a range of other fauna. Of all possible dugong sightings, 95% (CI = 90%, 98%) were subjectively classed as 'certain' (unmistakably dugongs). Neither our dugong sighting rate, nor our ability to identify dugongs with certainty, were affected by UAV altitude. Turbidity was the only environmental variable significantly affecting the dugong sighting rate. Our results suggest that UAV systems may not be limited by sea state conditions in the same manner as sightings from manned surveys. The overlap between images proved valuable for detecting animals that were masked by sun glitter in the corners of images, and identifying animals initially captured at awkward body angles. This initial trial of a basic camera system has successfully demonstrated that the ScanEagle UAV has great potential as a tool for marine mammal aerial surveys.

Unmanned Aerial Vehicles (UAVs) for Surveying Marine Fauna: A Dugong Case Study

PubMed Central

Hodgson, Amanda; Kelly, Natalie; Peel, David

2013-01-01

Aerial surveys of marine mammals are routinely conducted to assess and monitor species’ habitat use and population status. In Australia, dugongs (Dugong dugon) are regularly surveyed and long-term datasets have formed the basis for defining habitat of high conservation value and risk assessments of human impacts. Unmanned aerial vehicles (UAVs) may facilitate more accurate, human-risk free, and cheaper aerial surveys. We undertook the first Australian UAV survey trial in Shark Bay, western Australia. We conducted seven flights of the ScanEagle UAV, mounted with a digital SLR camera payload. During each flight, ten transects covering a 1.3 km2 area frequently used by dugongs, were flown at 500, 750 and 1000 ft. Image (photograph) capture was controlled via the Ground Control Station and the capture rate was scheduled to achieve a prescribed 10% overlap between images along transect lines. Images were manually reviewed post hoc for animals and scored according to sun glitter, Beaufort Sea state and turbidity. We captured 6243 images, 627 containing dugongs. We also identified whales, dolphins, turtles and a range of other fauna. Of all possible dugong sightings, 95% (CI = 90%, 98%) were subjectively classed as ‘certain’ (unmistakably dugongs). Neither our dugong sighting rate, nor our ability to identify dugongs with certainty, were affected by UAV altitude. Turbidity was the only environmental variable significantly affecting the dugong sighting rate. Our results suggest that UAV systems may not be limited by sea state conditions in the same manner as sightings from manned surveys. The overlap between images proved valuable for detecting animals that were masked by sun glitter in the corners of images, and identifying animals initially captured at awkward body angles. This initial trial of a basic camera system has successfully demonstrated that the ScanEagle UAV has great potential as a tool for marine mammal aerial surveys. PMID:24223967

Improved quantification of mountain snowpack properties using observations from Unmanned Air Vehicles (UAVs)

NASA Astrophysics Data System (ADS)

Shea, J. M.; Harder, P.; Pomeroy, J. W.; Kraaijenbrink, P. D. A.

2017-12-01

Mountain snowpacks represent a critical seasonal reservoir of water for downstream needs, and snowmelt is a significant component of mountain hydrological budgets. Ground-based point measurements are unable to describe the full spatial variability of snow accumulation and melt rates, and repeat Unmanned Air Vehicle (UAV) surveys provide an unparalleled opportunity to measure snow accumulation, redistribution and melt in alpine environments. This study presents results from a UAV-based observation campaign conducted at the Fortress Mountain Snow Laboratory in the Canadian Rockies in 2017. Seven survey flights were conducted between April (maximum snow accumulation) and mid-July (bare ground) to collect imagery with both an RGB camera and thermal infrared imager with the sensefly eBee RTK platform. UAV imagery are processed with structure from motion techniques, and orthoimages, digital elevation models, and surface temperature maps are validated against concurrent ground observations of snow depth, snow water equivalent, and snow surface temperature. We examine the seasonal evolution of snow depth and snow surface temperature, and explore the spatial covariances of these variables with respect to topographic factors and snow ablation rates. Our results have direct implications for scaling snow ablation calculations and model resolution and discretization.

High-Capacity Free-Space Optical Communications Between a Ground Transmitter and a Ground Receiver via a UAV Using Multiplexing of Multiple Orbital-Angular-Momentum Beams.

PubMed

Li, Long; Zhang, Runzhou; Zhao, Zhe; Xie, Guodong; Liao, Peicheng; Pang, Kai; Song, Haoqian; Liu, Cong; Ren, Yongxiong; Labroille, Guillaume; Jian, Pu; Starodubov, Dmitry; Lynn, Brittany; Bock, Robert; Tur, Moshe; Willner, Alan E

2017-12-12

We explore the use of orbital-angular-momentum (OAM)-multiplexing to increase the capacity of free-space data transmission to moving platforms, with an added potential benefit of decreasing the probability of data intercept. Specifically, we experimentally demonstrate and characterize the performance of an OAM-multiplexed, free-space optical (FSO) communications link between a ground transmitter and a ground receiver via a moving unmanned-aerial-vehicle (UAV). We achieve a total capacity of 80 Gbit/s up to 100-m-roundtrip link by multiplexing 2 OAM beams, each carrying a 40-Gbit/s quadrature-phase-shift-keying (QPSK) signal. Moreover, we investigate for static, hovering, and moving conditions the effects of channel impairments, including: misalignments, propeller-induced airflows, power loss, intermodal crosstalk, and system bit error rate (BER). We find the following: (a) when the UAV hovers in the air, the power on the desired mode fluctuates by 2.1 dB, while the crosstalk to the other mode is -19 dB below the power on the desired mode; and (b) when the UAV moves in the air, the power fluctuation on the desired mode increases to 4.3 dB and the crosstalk to the other mode increases to -10 dB. Furthermore, the channel crosstalk decreases with an increase in OAM mode spacing.

The UAV: A unique platform for electrodynamic studies of upward lightning in the middle atmosphere

NASA Technical Reports Server (NTRS)

Goldberg, Richard A.; Desch, Michael D.; Farrell, William M.

1997-01-01

The use of unmanned aerial vehicles (UAVs), a platform for investigations in an environment hostile to manned spacecraft, is discussed. A program which includes the use of UAVs coupled with ground-based measurements to conduct scientific studies on the electrical state of the atmosphere during electrically active periods is proposed. The radiating power from alternate current and transient components of the storm electrification was investigated.

Wetland Assessment Using Unmanned Aerial Vehicle (uav) Photogrammetry

NASA Astrophysics Data System (ADS)

Boon, M. A.; Greenfield, R.; Tesfamichael, S.

2016-06-01

The use of Unmanned Arial Vehicle (UAV) photogrammetry is a valuable tool to enhance our understanding of wetlands. Accurate planning derived from this technological advancement allows for more effective management and conservation of wetland areas. This paper presents results of a study that aimed at investigating the use of UAV photogrammetry as a tool to enhance the assessment of wetland ecosystems. The UAV images were collected during a single flight within 2½ hours over a 100 ha area at the Kameelzynkraal farm, Gauteng Province, South Africa. An AKS Y-6 MKII multi-rotor UAV and a digital camera on a motion compensated gimbal mount were utilised for the survey. Twenty ground control points (GCPs) were surveyed using a Trimble GPS to achieve geometrical precision and georeferencing accuracy. Structure-from-Motion (SfM) computer vision techniques were used to derive ultra-high resolution point clouds, orthophotos and 3D models from the multi-view photos. The geometric accuracy of the data based on the 20 GCP's were 0.018 m for the overall, 0.0025 m for the vertical root mean squared error (RMSE) and an over all root mean square reprojection error of 0.18 pixel. The UAV products were then edited and subsequently analysed, interpreted and key attributes extracted using a selection of tools/ software applications to enhance the wetland assessment. The results exceeded our expectations and provided a valuable and accurate enhancement to the wetland delineation, classification and health assessment which even with detailed field studies would have been difficult to achieve.

Roadside IED detection using subsurface imaging radar and rotary UAV

NASA Astrophysics Data System (ADS)

Qin, Yexian; Twumasi, Jones O.; Le, Viet Q.; Ren, Yu-Jiun; Lai, C. P.; Yu, Tzuyang

2016-05-01

Modern improvised explosive device (IED) and mine detection sensors using microwave technology are based on ground penetrating radar operated by a ground vehicle. Vehicle size, road conditions, and obstacles along the troop marching direction limit operation of such sensors. This paper presents a new conceptual design using a rotary unmanned aerial vehicle (UAV) to carry subsurface imaging radar for roadside IED detection. We have built a UAV flight simulator with the subsurface imaging radar running in a laboratory environment and tested it with non-metallic and metallic IED-like targets. From the initial lab results, we can detect the IED-like target 10-cm below road surface while carried by a UAV platform. One of the challenges is to design the radar and antenna system for a very small payload (less than 3 lb). The motion compensation algorithm is also critical to the imaging quality. In this paper, we also demonstrated the algorithm simulation and experimental imaging results with different IED target materials, sizes, and clutters.

Multi-temporal UAV based data for mapping crop type and structure in smallholder dominated Tanzanian agricultural landscape

NASA Astrophysics Data System (ADS)

Nagol, J. R.; Chung, C.; Dempewolf, J.; Maurice, S.; Mbungu, W.; Tumbo, S.

2015-12-01

Timely mapping and monitoring of crops like Maize, an important food security crop in Tanzania, can facilitate timely response by government and non-government organizations to food shortage or surplus conditions. Small UAVs can play an important role in linking the spaceborne remote sensing data and ground based measurement to improve the calibration and validation of satellite based estimates of in-season crop metrics. In Tanzania most of the growing season is often obscured by clouds. UAV data, if collected within a stratified statistical sampling framework, can also be used to directly in lieu of spaceborne data to infer mid-season yield estimates at regional scales.Here we present an object based approach to estimate crop metrics like crop type, area, and height using multi-temporal UAV based imagery. The methods were tested at three 1km2 plots in Kilosa, Njombe, and Same districts in Tanzania. At these sites both ground based and UAV based data were collected on a monthly time-step during the year 2015 growing season. SenseFly eBee drone with RGB and NIR-R-G camera was used to collect data. Crop type classification accuracies of above 85% were easily achieved.

A Two-Echelon Cooperated Routing Problem for a Ground Vehicle and Its Carried Unmanned Aerial Vehicle.

PubMed

Luo, Zhihao; Liu, Zhong; Shi, Jianmai

2017-05-17

In this paper, a two-echelon cooperated routing problem for the ground vehicle (GV) and its carried unmanned aerial vehicle (UAV) is investigated, where the GV travels on the road network and its UAV travels in areas beyond the road to visit a number of targets unreached by the GV. In contrast to the classical two-echelon routing problem, the UAV has to launch and land on the GV frequently to change or charge its battery while the GV is moving on the road network. A new 0-1 integer programming model is developed to formulate the problem, where the constraints on the spatial and temporal cooperation of GV and UAV routes are included. Two heuristics are proposed to solve the model: the first heuristic (H1) constructs a complete tour for all targets and splits it by GV routes, while the second heuristic (H2) constructs the GV tour and assigns UAV flights to it. Random instances with six different sizes (25-200 targets, 12-80 rendezvous nodes) are used to test the algorithms. Computational results show that H1 performs slightly better than H2, while H2 uses less time and is more stable.

Evaluation of Bare Ground on Rangelands using Unmanned Aerial Vehicles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robert P. Breckenridge; Maxine Dakins

2011-01-01

Attention is currently being given to methods that assess the ecological condition of rangelands throughout the United States. There are a number of different indicators that assess ecological condition of rangelands. Bare Ground is being considered by a number of agencies and resource specialists as a lead indicator that can be evaluated over a broad area. Traditional methods of measuring bare ground rely on field technicians collecting data along a line transect or from a plot. Unmanned aerial vehicles (UAVs) provide an alternative to collecting field data, can monitor a large area in a relative short period of time, andmore » in many cases can enhance safety and time required to collect data. In this study, both fixed wing and helicopter UAVs were used to measure bare ground in a sagebrush steppe ecosystem. The data were collected with digital imagery and read using the image analysis software SamplePoint. The approach was tested over seven different plots and compared against traditional field methods to evaluate accuracy for assessing bare ground. The field plots were located on the Idaho National Laboratory (INL) site west of Idaho Falls, Idaho in locations where there is very little disturbance by humans and the area is grazed only by wildlife. The comparison of fixed-wing and helicopter UAV technology against field estimates shows good agreement for the measurement of bare ground. This study shows that if a high degree of detail and data accuracy is desired, then a helicopter UAV may be a good platform. If the data collection objective is to assess broad-scale landscape level changes, then the collection of imagery with a fixed-wing system is probably more appropriate.« less

An Innovative Unmanned System for Advanced Environmental Monitoring: Design and Development

NASA Astrophysics Data System (ADS)

Marsella, Ennio; Giordano, Laura; Evangelista, Lorenza; Iengo, Antonio; di Filippo, Alessandro; Coppola, Aniello

2015-04-01

The paper summarizes the design and development of a new technology and tools for real-time coordination and control of unmanned vehicles for advanced environmental monitoring. A new Unmanned System has been developed at Institute for Coastal Marine Environmental - National Research Council (Italy), in the framework of two National Operational Programs (PON): Technological Platform for Geophysical and Environmental Marine Survey-PITAM and Integrated Systems and Technologies for Geophysical and Environmental Monitoring in coastal-marine areas-STIGEAC. In particular, the system includes one Unmanned Aerial Vehicle (UAV) and two Unmanned Marine Vehicles (UMV). Major innovations concern the implementation of a new architecture to control each drone and/or to allow the cooperation between heterogeneous vehicles, the integration of distributed sensing techniques and real-time image processing capabilities. Part of the research in these projects involves, therefore, an architecture, where the ground operator can communicate with the Unmanned Vehicles at various levels of abstraction using pointing devices and video viewing. In detail, a Ground Control Station (GCS) has been design and developed to allow the government in security of the drones within a distance up to twenty kilometers for air explorations and within ten nautical miles for marine activities. The Ground Control Station has the following features: 1. hardware / software system for the definition of the mission profiles; 3. autonomous and semi-autonomous control system by remote control (joystick or other) for the UAV and UMVs; 4. integrated control system with comprehensive visualization capabilities, monitoring and archiving of real-time data acquired from scientific payload; 5. open structure to future additions of systems, sensors and / or additional vehicles. In detail, the UAV architecture is a dual-rotor, with an endurance ranging from 55 to 200 minutes, depending on payload weight (maximum 26 kg) and wind conditions, and a capability to survey an area of up to 5x5 square kilometers. The UAV payload consists of three different types of sensors: a laser scanner, a thermal-camera and an integrated camera reflex with gimbal. The laser scanner has 10 mm survey-grade accuracy and a field of view up to 330°. The thermal-camera has a resolution 640x480 pixels and a thermal sensitivity <20 mK (at 30 °C), while the reflex is a 22.3 Megapixel full-frame sensor. In addition to the common applications, such as generating mapping, charting, and geodesy products, the system allows performing real-time survey and monitoring of different natural risk under dangerous condition. The system is, also, address to environmental risk monitoring and prevention, industrial activity and emergency interventions related to environmental crises (i.e. oil spills).

LiDAR and Image Point Cloud Comparison

DTIC Science & Technology

2014-09-01

UAV unmanned aerial vehicle USGS United States Geological Survey UTM Universal Transverse Mercator WGS 84 World Geodetic System 1984 WSI...19  1.  Physics of LiDAR Systems ................................................................20  III.  DATA AND SOFTWARE...ground control point GPS Global Positioning System IMU inertial measurements unit LiDAR light detection and ranging MI mutual information MVS

Improving geolocation and spatial accuracies with the modular integrated avionics group (MIAG)

NASA Astrophysics Data System (ADS)

Johnson, Einar; Souter, Keith

1996-05-01

The modular integrated avionics group (MIAG) is a single unit approach to combining position, inertial and baro-altitude/air data sensors to provide optimized navigation, guidance and control performance. Lear Astronics Corporation is currently working within the navigation community to upgrade existing MIAG performance with precise GPS positioning mechanization tightly integrated with inertial, baro and other sensors. Among the immediate benefits are the following: (1) accurate target location in dynamic conditions; (2) autonomous launch and recovery using airborne avionics only; (3) precise flight path guidance; and (4) improved aircraft and payload stability information. This paper will focus on the impact of using the MIAG with its multimode navigation accuracies on the UAV targeting mission. Gimbaled electro-optical sensors mounted on a UAV can be used to determine ground coordinates of a target at the center of the field of view by a series of vector rotation and scaling computations. The accuracy of the computed target coordinates is dependent on knowing the UAV position and the UAV-to-target offset computation. Astronics performed a series of simulations to evaluate the effects that the improved angular and position data available from the MIAG have on target coordinate accuracy.

Rapid mapping of landslide disaster using UAV- photogrammetry

NASA Astrophysics Data System (ADS)

Cahyono, A. B.; Zayd, R. A.

2018-03-01

Unmanned Aerial Vehicle (UAV) systems offered many advantages in several mapping applications such as slope mapping, geohazard studies, etc. This study utilizes UAV system for landslide disaster occurred in Jombang Regency, East Java. This study concentrates on type of rotor-wing UAV, that is because rotor wing units are stable and able to capture images easily. Aerial photograph were acquired in the form of strips which followed the procedure of acquiring aerial photograph where taken 60 photos. Secondary data of ground control points using GPS Geodetic and check points established using Total Station technique was used. The digital camera was calibrated using close range photogrammetric software and the recovered camera calibration parameters were then used in the processing of digital images. All the aerial photographs were processed using digital photogrammetric software and the output in the form of orthophoto was produced. The final result shows a 1: 1500 scale orthophoto map from the data processing with SfM algorithm with GSD accuracy of 3.45 cm. And the calculated volume of contour line delineation of 10527.03 m3. The result is significantly different from the result of terrestrial methode equal to 964.67 m3 or 8.4% of the difference of both.

Assessing the consistency of UAV-derived point clouds and images acquired at different altitudes

NASA Astrophysics Data System (ADS)

Ozcan, O.

2016-12-01

Unmanned Aerial Vehicles (UAVs) offer several advantages in terms of cost and image resolution compared to terrestrial photogrammetry and satellite remote sensing system. Nowadays, UAVs that bridge the gap between the satellite scale and field scale applications were initiated to be used in various application areas to acquire hyperspatial and high temporal resolution imageries due to working capacity and acquiring in a short span of time with regard to conventional photogrammetry methods. UAVs have been used for various fields such as for the creation of 3-D earth models, production of high resolution orthophotos, network planning, field monitoring and agricultural lands as well. Thus, geometric accuracy of orthophotos and volumetric accuracy of point clouds are of capital importance for land surveying applications. Correspondingly, Structure from Motion (SfM) photogrammetry, which is frequently used in conjunction with UAV, recently appeared in environmental sciences as an impressive tool allowing for the creation of 3-D models from unstructured imagery. In this study, it was aimed to reveal the spatial accuracy of the images acquired from integrated digital camera and the volumetric accuracy of Digital Surface Models (DSMs) which were derived from UAV flight plans at different altitudes using SfM methodology. Low-altitude multispectral overlapping aerial photography was collected at the altitudes of 30 to 100 meters and georeferenced with RTK-GPS ground control points. These altitudes allow hyperspatial imagery with the resolutions of 1-5 cm depending upon the sensor being used. Preliminary results revealed that the vertical comparison of UAV-derived point clouds with respect to GPS measurements pointed out an average distance at cm-level. Larger values are found in areas where instantaneous changes in surface are present.

Combined Study of Snow Depth Determination and Winter Leaf Area Index Retrieval by Unmanned Aerial Vehicle Photogrammetry

NASA Astrophysics Data System (ADS)

Lendzioch, Theodora; Langhammer, Jakub; Jenicek, Michal

2017-04-01

A rapid and robust approach using Unmanned Aerial Vehicle (UAV) digital photogrammetry was performed for evaluating snow accumulation over different small localities (e.g. disturbed forest and open area) and for indirect field measurements of Leaf Area Index (LAI) of coniferous forest within the Šumava National Park, Czech Republic. The approach was used to reveal impacts related to changes in forest and snowpack and to determine winter effective LAI for monitoring the impact of forest canopy metrics on snow accumulation. Due to the advancement of the technique, snow depth and volumetric changes of snow depth over these selected study areas were estimated at high spatial resolution (1 cm) by subtracting a snow-free digital elevation model (DEM) from a snow-covered DEM. Both, downward-looking UAV images and upward-looking digital hemispherical photography (DHP), and additional widely used LAI-2200 canopy analyser measurements were applied to determine the winter LAI, controlling interception and transmitting radiation. For the performance of downward-looking UAV images the snow background instead of the sky fraction was used. The reliability of UAV-based LAI retrieval was tested by taking an independent data set during the snow cover mapping campaigns. The results showed the potential of digital photogrammetry for snow depth mapping and LAI determination by UAV techniques. The average difference obtained between ground-based and UAV-based measurements of snow depth was 7.1 cm with higher values obtained by UAV. The SD of 22 cm for the open area seemed competitive with the typical precision of point measurements. In contrast, the average difference in disturbed forest area was 25 cm with lower values obtained by UAV and a SD of 36 cm, which is in agreement with other studies. The UAV-based LAI measurements revealed the lowest effective LAI values and the plant canopy analyser LAI-2200 the highest effective LAI values. The biggest bias of effective LAI was observed between LAI-2200 and UAV-based analyses. Since the LAI parameter is important for snowpack modelling, this method presents the potential of simplifying LAI retrieval and mapping of snow dynamics while reducing running costs and time.

Wind and Wake Sensing with UAV Formation Flight: System Development and Flight Testing

NASA Astrophysics Data System (ADS)

Larrabee, Trenton Jameson

Wind turbulence including atmospheric turbulence and wake turbulence have been widely investigated; however, only recently it become possible to use Unmanned Aerial Vehicles (UAVs) as a validation tool for research in this area. Wind can be a major contributing factor of adverse weather for aircraft. More importantly, it is an even greater risk towards UAVs because of their small size and weight. Being able to estimate wind fields and gusts can potentially provide substantial benefits for both unmanned and manned aviation. Possible applications include gust suppression for improving handling qualities, a better warning system for high wind encounters, and enhanced control for small UAVs during flight. On the other hand, the existence of wind can be advantageous since it can lead to fuel savings and longer duration flights through dynamic soaring or thermal soaring. Wakes are an effect of the lift distribution across an aircraft's wing or tail. Wakes can cause substantial disturbances when multiple aircraft are moving through the same airspace. In fact, the perils from an aircraft flying through the wake of another aircraft is a leading cause of the delay between takeoff times at airports. Similar to wind, though, wakes can be useful for energy harvesting and increasing an aircraft's endurance when flying in formation which can be a great advantage to UAVs because they are often limited in flight time due to small payload capacity. Formation flight can most often be seen in manned aircraft but can be adopted for use with unmanned systems. Autonomous flight is needed for flying in the "sweet spot" of the generated wakes for energy harvesting as well as for thermal soaring during long duration flights. For the research presented here formation flight was implemented for the study of wake sensing and gust alleviation. The major contributions of this research are in the areas of a novel technique to estimate wind using an Unscented Kalman filter and experimental wake sensing data using UAVs in formation flight. This has been achieved and well documented before in manned aircraft but very little work has been done on UAV wake sensing especially during flight testing. This document describes the development and flight testing of small unmanned aerial system (UAS) for wind and wake sensing purpose including a Ground Control Station (GCS) and UAVs. This research can be stated in four major components. Firstly, formation flight was obtained by integrating a formation flight controller on the WVU Phastball Research UAV aircraft platform from the Flight Control Systems Laboratory (FCSL) at West Virginia University (WVU). Second, a new approach to wind estimation using an Unscented Kalman filter (UKF) is discussed along with results from flight data. Third, wake modeling within a simulator and wake sensing during formation flight is shown. Finally, experimental results are used to discuss the "sweet spot" for energy harvesting in formation flight, a novel approach to cooperative wind estimation, and gust suppression control for a follower aircraft in formation flight.

About infrared scanning of photovoltaic solar plant

NASA Astrophysics Data System (ADS)

Kauppinen, T.; Panouillot, P.-E.; Siikanen, S.; Athanasakou, E.; Baltas, P.; Nikopoulous, B.

2015-05-01

The paper is discussing about infrared scanning of PV solar plants. It is important that the performance of each solar panel and cell is verified. One new possibility compared to traditional ground-based scanning (handheld camera) is the utilization of UAV (Unmanned Aerial Vehicle). In this paper results from a PV solar Plant in Western Greece are introduced. The nominal power of the solar plants were 0, 9 MW and 2 MW and they were scanned both by a ground-controlled drone and by handheld equipment. It is essential to know all the factors effecting to results and also the time of scanning is important. The results done from the drone and from ground-based scanning are compared; also results from various altitudes and time of day are discussed. The UAV (Unmanned Aerial Vehicle/RPAS (Remote Piloted Aircraft Systems) will give an excellent opportunity to monitor various targets which are impossible or difficult to access from the ground. Compared to fixed-wing and helicopter-based platforms it will give advantages but also this technology has limitations. One limitation is the weight of the equipment and the short operational range and short flight time. Also valid procedures must be created for different solutions in the future. The most important thing, as in all infrared thermography applications, is the proper interpretation of results.

The application of micro UAV in construction project

NASA Astrophysics Data System (ADS)

Kaamin, Masiri; Razali, Siti Nooraiin Mohd; Ahmad, Nor Farah Atiqah; Bukari, Saifullizan Mohd; Ngadiman, Norhayati; Kadir, Aslila Abd; Hamid, Nor Baizura

2017-10-01

In every outstanding construction project, there is definitely have an effective construction management. Construction management allows a construction project to be implemented according to plan. Every construction project must have a progress development works that is usually created by the site engineer. Documenting the progress of works is one of the requirements in construction management. In a progress report it is necessarily have a visual image as an evidence. The conventional method used for photographing on the construction site is by using common digital camera which is has few setback comparing to Micro Unmanned Aerial Vehicles (UAV). Besides, site engineer always have a current issues involving limitation of monitoring on high reach point and entire view of the construction site. The purpose of this paper is to provide a concise review of Micro UAV technology in monitoring the progress on construction site through visualization approach. The aims of this study are to replace the conventional method of photographing on construction site using Micro UAV which can portray the whole view of the building, especially on high reach point and allows to produce better images, videos and 3D model and also facilitating site engineer to monitor works in progress. The Micro UAV was flown around the building construction according to the Ground Control Points (GCPs) to capture images and record videos. The images taken from Micro UAV have been processed generate 3D model and were analysed to visualize the building construction as well as monitoring the construction progress work and provides immediate reliable data for project estimation. It has been proven that by using Micro UAV, a better images and videos can give a better overview of the construction site and monitor any defects on high reach point building structures. Not to be forgotten, with Micro UAV the construction site progress is more efficiently tracked and kept on the schedule.

Opportunities provided by UAVs to monitor erosion processes in agricultural catchments: a case study from Northern France

NASA Astrophysics Data System (ADS)

Frankl, Amaury; Stal, Cornelis; De Wit, Bart; De Wulf, Alain; Salvador, Pierre-Gil; Nyssen, Jan

2014-05-01

In erosion studies, accurate spatio-temporal data are required to fully understand the processes involved and their relationship with environmental controls. With cameras being mounted on Unmanned Aerial Vehicles (UAVs), the latter allow to collect low-altitude aerial photographs over small catchments in a cost-effective and rapid way. From large data sets of overlapping aerial photographs, Structure from Motion - Multi View Stereo workflows, integrated in various software such as PhotoScan used here, allow to produced detailed Digital Surface Models (DSMs) and ortho-mosaics. In this study we present the results from a survey carried out in a small agricultural catchment near Hallines, in Northern France. A DSM and ortho-mosaic was produced of the catchment using photographs taken from a low-cost radio-controlled microdrone (DroneFlyer Hexacopter). Photographs were taken with a Sony Nex 5 (16.1 M pixels) camera having a fixed normal lens of 50 mm. In the field, Ground Control Points were materialized by unambiguously determinable targets, measured with a 1'' total station (Leica TS15i). Cross-sections of rills and ephemeral gullies were also quantified from total station measurements and from terrestrial image-based 3D modelling. These data allowed to define the accuracy of the DSM and the representation of the erosion features in it. The feasibility of UAVs photographic surveys to improve our understanding on water-erosion processes such as sheet, rill and gully erosion is discussed. Keywords: Ephemeral gully, Erosion study, Image-based 3D modelling, Microdrone, Rill, UAVs.

A Two-Echelon Cooperated Routing Problem for a Ground Vehicle and Its Carried Unmanned Aerial Vehicle

PubMed Central

Luo, Zhihao; Liu, Zhong; Shi, Jianmai

2017-01-01

In this paper, a two-echelon cooperated routing problem for the ground vehicle (GV) and its carried unmanned aerial vehicle (UAV) is investigated, where the GV travels on the road network and its UAV travels in areas beyond the road to visit a number of targets unreached by the GV. In contrast to the classical two-echelon routing problem, the UAV has to launch and land on the GV frequently to change or charge its battery while the GV is moving on the road network. A new 0–1 integer programming model is developed to formulate the problem, where the constraints on the spatial and temporal cooperation of GV and UAV routes are included. Two heuristics are proposed to solve the model: the first heuristic (H1) constructs a complete tour for all targets and splits it by GV routes, while the second heuristic (H2) constructs the GV tour and assigns UAV flights to it. Random instances with six different sizes (25–200 targets, 12–80 rendezvous nodes) are used to test the algorithms. Computational results show that H1 performs slightly better than H2, while H2 uses less time and is more stable. PMID:28513552

Unmanned aerial vehicle (UAV)-based monitoring of a landslide: Gallenzerkogel landslide (Ybbs-Lower Austria) case study.

PubMed

Eker, Remzi; Aydın, Abdurrahim; Hübl, Johannes

2017-12-19

In the present study, UAV-based monitoring of the Gallenzerkogel landslide (Ybbs, Lower Austria) was carried out by three flight missions. High-resolution digital elevation models (DEMs), orthophotos, and density point clouds were generated from UAV-based aerial photos via structure-from-motion (SfM). According to ground control points (GCPs), an average of 4 cm root mean square error (RMSE) was found for all models. In addition, light detection and ranging (LIDAR) data from 2009, representing the prefailure topography, was utilized as a digital terrain model (DTM) and digital surface model (DSM). First, the DEM of difference (DoD) between the first UAV flight data and the LIDAR-DTM was determined and according to the generated DoD deformation map, an elevation difference of between - 6.6 and 2 m was found. Over the landslide area, a total of 4380.1 m 3 of slope material had been eroded, while 297.4 m 3 of the material had accumulated within the most active part of the slope. In addition, 688.3 m 3 of the total eroded material had belonged to the road destroyed by the landslide. Because of the vegetation surrounding the landslide area, the Multiscale Model-to-Model Cloud Comparison (M3C2) algorithm was then applied to compare the first and second UAV flight data. After eliminating both the distance uncertainty values of higher than 15 cm and the nonsignificant changes, the M3C2 distance obtained was between - 2.5 and 2.5 m. Moreover, the high-resolution orthophoto generated by the third flight allowed visual monitoring of the ongoing control/stabilization work in the area.

Ikhana: A NASA Unmanned Aerial System Supporting Long-Duration Earth Science Missions

NASA Technical Reports Server (NTRS)

Cobleigh, Brent R.

2007-01-01

This viewgraph presentation reviews Ikhana's project goals: (1) Develop an airborne platform to conduct Earth observation and atmospheric sampling science missions both nationally and internationally, (2) develop and demonstrate technologies that improve the capability of UAVs to conduct science collection missions, (3) develop technologies that improve manned and unmanned aircraft systems, and (4) support important national UAV development activities. The criteria that guided the selection of the aircraft are listed. The payload areas on Ikhana are shown and the network that connects the systems are also reviewed. The data recorder is shown. Also the diagram of the Airborne Research Test System (ARTS) is reviewed. The Mobile Ground Control Station and the Mobile Ku SatCom Antenna are also shown and described.

Assessing the Flight Quality of a Large UAV for Sensors/Ground Robots Aerial Delivery

DTIC Science & Technology

2010-09-01

Lycoming 0320 - 0360 - Continental 0200 or any 100- 200hp 8. Wheels/ Brakes — Matco only 9. Wing skins — 2024-T3 alclad aircraft grade only (No...with full span trim 18. Rivets — Steel/steel and zinc plated pull type rivet 19. Rudder pedals — Dual rudder pedals toe brakes 20. Control systems

UAV Applications for Thermodynamic Profiling:Emphasis on Ice Fog Visibility

NASA Astrophysics Data System (ADS)

Gultepe, Ismail; Heymsfield, Andrew; Fernando, Joseph; hoch, sebastian; pardyjack, Eric; Boudala, faisal; Ware, Randolph

2017-04-01

Ice fog often occurs over the Arctic, in cold climates, and near mountainous regions about 30% of time when temperatures (T) drop to -10°C or below. Ice fog affects aviation operations, transportation, and local climate. Ice Nucleation (IN) and radiative cooling play an important role by controlling the intensity of ice fog conditions. Ice fog can also occur at T above -10°C, but close to 0°C it mainly occurs due to freezing of supercooled droplets that contain an IN. To better document ice fog conditions, observations from ice fog events of the Indirect and Semi-Direct Aerosol effects on Climate (ISDAC) project (Barrow, Alaska), Fog Remote Sensing And Modeling (FRAM) project (Yellowknife, Northwest Territories), and the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) project (Heber City, Utah), were analyzed. Difficulties in measuring small ice fog particles at low temperatures and low-level research aircraft flying restrictions prevent observations from aircraft within the atmospheric boundary layer. However, Unmanned Aerial Vehicles (UAVs) can be operated safely to measure IN number concentration, Relative Humidity with respect to ice (RHi), T, horizontal wind speed (Uh) and direction, visibility, and possibly even measuring ice crystal spectra below about 500 micron, to provide a method for future research of ice fog. In this study, thermodynamic profiling was conducted using a Radiometrics Microwave Radiometer (PMWR) and Vaisala CL51 ceilometer to describe vertical spatial and temporal development of ice fog conditions. Overall, ice fog characteristics and its thermodynamic environment will be presented using both ground-based and airborne platforms such as a UAV with new sensors. Some examples of measurements from the UAV and a DMT GCIP (Droplet Measurement Technologies Ground Cloud Imaging Probe), and challenges related to both ice fog measurements and visibility parameterization will also be presented.

Unmanned aerial vehicle: A unique platform for low-altitude remote sensing for crop management

USDA-ARS?s Scientific Manuscript database

Unmanned aerial vehicles (UAV) provide a unique platform for remote sensing to monitor crop fields that complements remote sensing from satellite, aircraft and ground-based platforms. The UAV-based remote sensing is versatile at ultra-low altitude to be able to provide an ultra-high-resolution imag...

Deep convolutional neural network for classifying Fusarium wilt of radish from unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Ha, Jin Gwan; Moon, Hyeonjoon; Kwak, Jin Tae; Hassan, Syed Ibrahim; Dang, Minh; Lee, O. New; Park, Han Yong

2017-10-01

Recently, unmanned aerial vehicles (UAVs) have gained much attention. In particular, there is a growing interest in utilizing UAVs for agricultural applications such as crop monitoring and management. We propose a computerized system that is capable of detecting Fusarium wilt of radish with high accuracy. The system adopts computer vision and machine learning techniques, including deep learning, to process the images captured by UAVs at low altitudes and to identify the infected radish. The whole radish field is first segmented into three distinctive regions (radish, bare ground, and mulching film) via a softmax classifier and K-means clustering. Then, the identified radish regions are further classified into healthy radish and Fusarium wilt of radish using a deep convolutional neural network (CNN). In identifying radish, bare ground, and mulching film from a radish field, we achieved an accuracy of ≥97.4%. In detecting Fusarium wilt of radish, the CNN obtained an accuracy of 93.3%. It also outperformed the standard machine learning algorithm, obtaining 82.9% accuracy. Therefore, UAVs equipped with computational techniques are promising tools for improving the quality and efficiency of agriculture today.

Near Real Time Structural Health Monitoring with Multiple Sensors in a Cloud Environment

NASA Astrophysics Data System (ADS)

Bock, Y.; Todd, M.; Kuester, F.; Goldberg, D.; Lo, E.; Maher, R.

2017-12-01

A repeated near real time 3-D digital surrogate representation of critical engineered structures can be used to provide actionable data on subtle time-varying displacements in support of disaster resiliency. We describe a damage monitoring system of optimally-integrated complementary sensors, including Global Navigation Satellite Systems (GNSS), Micro-Electro-Mechanical Systems (MEMS) accelerometers coupled with the GNSS (seismogeodesy), light multi-rotor Unmanned Aerial Vehicles (UAVs) equipped with high-resolution digital cameras and GNSS/IMU, and ground-based Light Detection and Ranging (LIDAR). The seismogeodetic system provides point measurements of static and dynamic displacements and seismic velocities of the structure. The GNSS ties the UAV and LIDAR imagery to an absolute reference frame with respect to survey stations in the vicinity of the structure to isolate the building response to ground motions. The GNSS/IMU can also estimate the trajectory of the UAV with respect to the absolute reference frame. With these constraints, multiple UAVs and LIDAR images can provide 4-D displacements of thousands of points on the structure. The UAV systematically circumnavigates the target structure, collecting high-resolution image data, while the ground LIDAR scans the structure from different perspectives to create a detailed baseline 3-D reference model. UAV- and LIDAR-based imaging can subsequently be repeated after extreme events, or after long time intervals, to assess before and after conditions. The unique challenge is that disaster environments are often highly dynamic, resulting in rapidly evolving, spatio-temporal data assets with the need for near real time access to the available data and the tools to translate these data into decisions. The seismogeodetic analysis has already been demonstrated in the NASA AIST Managed Cloud Environment (AMCE) designed to manage large NASA Earth Observation data projects on Amazon Web Services (AWS). The Cloud provides distinct advantages in terms of extensive storage and computing resources required for processing UAV and LIDAR imagery. Furthermore, it avoids single points of failure and allows for remote operations during emergencies, when near real time access to structures may be limited.

Spectral Imaging from Uavs Under Varying Illumination Conditions

NASA Astrophysics Data System (ADS)

Hakala, T.; Honkavaara, E.; Saari, H.; Mäkynen, J.; Kaivosoja, J.; Pesonen, L.; Pölönen, I.

2013-08-01

Rapidly developing unmanned aerial vehicles (UAV) have provided the remote sensing community with a new rapidly deployable tool for small area monitoring. The progress of small payload UAVs has introduced greater demand for light weight aerial payloads. For applications requiring aerial images, a simple consumer camera provides acceptable data. For applications requiring more detailed spectral information about the surface, a new Fabry-Perot interferometer based spectral imaging technology has been developed. This new technology produces tens of successive images of the scene at different wavelength bands in very short time. These images can be assembled in spectral data cubes with stereoscopic overlaps. On field the weather conditions vary and the UAV operator often has to decide between flight in sub optimal conditions and no flight. Our objective was to investigate methods for quantitative radiometric processing of images taken under varying illumination conditions, thus expanding the range of weather conditions during which successful imaging flights can be made. A new method that is based on insitu measurement of irradiance either in UAV platform or in ground was developed. We tested the methods in a precision agriculture application using realistic data collected in difficult illumination conditions. Internal homogeneity of the original image data (average coefficient of variation in overlapping images) was 0.14-0.18. In the corrected data, the homogeneity was 0.10-0.12 with a correction based on broadband irradiance measured in UAV, 0.07-0.09 with a correction based on spectral irradiance measurement on ground, and 0.05-0.08 with a radiometric block adjustment based on image data. Our results were very promising, indicating that quantitative UAV based remote sensing could be operational in diverse conditions, which is prerequisite for many environmental remote sensing applications.

Diverse Planning for UAV Control and Remote Sensing

PubMed Central

Tožička, Jan; Komenda, Antonín

2016-01-01

Unmanned aerial vehicles (UAVs) are suited to various remote sensing missions, such as measuring air quality. The conventional method of UAV control is by human operators. Such an approach is limited by the ability of cooperation among the operators controlling larger fleets of UAVs in a shared area. The remedy for this is to increase autonomy of the UAVs in planning their trajectories by considering other UAVs and their plans. To provide such improvement in autonomy, we need better algorithms for generating alternative trajectory variants that the UAV coordination algorithms can utilize. In this article, we define a novel family of multi-UAV sensing problems, solving task allocation of huge number of tasks (tens of thousands) to a group of configurable UAVs with non-zero weight of equipped sensors (comprising the air quality measurement as well) together with two base-line solvers. To solve the problem efficiently, we use an algorithm for diverse trajectory generation and integrate it with a solver for the multi-UAV coordination problem. Finally, we experimentally evaluate the multi-UAV sensing problem solver. The evaluation is done on synthetic and real-world-inspired benchmarks in a multi-UAV simulator. Results show that diverse planning is a valuable method for remote sensing applications containing multiple UAVs. PMID:28009831

Diverse Planning for UAV Control and Remote Sensing.

PubMed

Tožička, Jan; Komenda, Antonín

2016-12-21

Unmanned aerial vehicles (UAVs) are suited to various remote sensing missions, such as measuring air quality. The conventional method of UAV control is by human operators. Such an approach is limited by the ability of cooperation among the operators controlling larger fleets of UAVs in a shared area. The remedy for this is to increase autonomy of the UAVs in planning their trajectories by considering other UAVs and their plans. To provide such improvement in autonomy, we need better algorithms for generating alternative trajectory variants that the UAV coordination algorithms can utilize. In this article, we define a novel family of multi-UAV sensing problems, solving task allocation of huge number of tasks (tens of thousands) to a group of configurable UAVs with non-zero weight of equipped sensors (comprising the air quality measurement as well) together with two base-line solvers. To solve the problem efficiently, we use an algorithm for diverse trajectory generation and integrate it with a solver for the multi-UAV coordination problem. Finally, we experimentally evaluate the multi-UAV sensing problem solver. The evaluation is done on synthetic and real-world-inspired benchmarks in a multi-UAV simulator. Results show that diverse planning is a valuable method for remote sensing applications containing multiple UAVs.

Comparison of Unmanned Aerial Vehicle Platforms for Assessing Vegetation Cover in Sagebrush Steppe Ecosystems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robert P. Breckenridge; Maxine Dakins; Stephen Bunting

2011-09-01

In this study, the use of unmanned aerial vehicles (UAVs) as a quick and safe method for monitoring biotic resources was evaluated. Vegetation cover and the amount of bare ground are important factors in understanding the sustainability of many ecosystems and assessment of rangeland health. Methods that improve speed and cost efficiency could greatly improve how biotic resources are monitored on western lands. Sagebrush steppe ecosystems provide important habitat for a variety of species (including sage grouse and pygmy rabbit). Improved methods are needed to support monitoring these habitats because there are not enough resource specialists or funds available formore » comprehensive ground evaluations. In this project, two UAV platforms, fixed wing and helicopter, were used to collect still-frame imagery to assess vegetation cover in sagebrush steppe ecosystems. This paper discusses the process for collecting and analyzing imagery from the UAVs to (1) estimate percent cover for six different vegetation types (shrub, dead shrub, grass, forb, litter, and bare ground) and (2) locate sage grouse using representative decoys. The field plots were located on the Idaho National Engineering (INL) site west of Idaho Falls, Idaho, in areas with varying amounts and types of vegetation cover. A software program called SamplePoint was used along with visual inspection to evaluate percent cover for the six cover types. Results were compared against standard field measurements to assess accuracy. The comparison of fixed-wing and helicopter UAV technology against field estimates shows good agreement for the measurement of bare ground. This study shows that if a high degree of detail and data accuracy is desired, then a helicopter UAV may be a good platform to use. If the data collection objective is to assess broad-scale landscape level changes, then the collection of imagery with a fixed-wing system is probably more appropriate.« less

Feasibility Study for an Autonomous UAV -Magnetometer System -- Final Report on SERDP SEED 1509:2206

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roelof Versteeg; Mark McKay; Matt Anderson

2007-09-01

Large areas across the United States are potentially contaminated with UXO, with some ranges encompassing tens to hundreds of thousands of acres. Technologies are needed which will allow for cost effective wide area scanning with 1) near 100 % coverage and 2) near 100 % detection of subsurface ordnance or features indicative of subsurface ordnance. The current approach to wide area scanning is a multi-level one, in which medium altitude fixed wing optical imaging is used for an initial site assessment. This assessment is followed with low altitude manned helicopter based magnetometry followed by surface investigations using either towed geophysicalmore » sensor arrays or man portable sensors. In order to be effective for small UXO detection, the sensing altitude for magnetic site investigations needs to be on the order of 1 – 3 meters. These altitude requirements means that manned helicopter surveys will generally only be feasible in large, open and relatively flat terrains. While such surveys are effective in mapping large areas relatively fast there are substantial mobilization/demobilization, staffing and equipment costs associated with these surveys (resulting in costs of approximately $100-$150/acre). Surface towed arrays provide high resolution maps but have other limitations, e.g. in their ability to navigate rough terrain effectively. Thus, other systems are needed allowing for effective data collection. An UAV (Unmanned Aerial Vehicle) magnetometer platform is an obvious alternative. The motivation behind such a system is that it would be safer for the operators, cheaper in initial and O&M costs, and more effective in terms of site characterization. However, while UAV data acquisition from fixed wing platforms for large (> 200 feet) stand off distances is relatively straight forward, a host of challenges exist for low stand-off distance (~ 6 feet) UAV geophysical data acquisition. The objective of SERDP SEED 1509:2006 was to identify the primary challenges associated with a low stand off distance autonomous UAV magnetometer platform and to investigate whether these challenges can be resolved successfully such that a successful UAV magnetometer platform can be constructed. The primary challenges which were identified and investigated include: 1. The feasibility of assembling a payload package which integrates magnetometers, accurate positioning systems (DGPS, height above ground measurement), obstacle avoidance systems, power infrastructure, communications and data storage as well as auxiliary flight controls 2. The availability of commercial UAV platforms with autonomous flight capability which can accommodate this payload package 3. The feasibility of integrating obstacle avoidance controls in UAV platform control 4. The feasibility of collecting high quality magnetic data in the vicinity of an UAV.« less

Multi-UAV Routing for Area Coverage and Remote Sensing with Minimum Time

PubMed Central

Avellar, Gustavo S. C.; Pereira, Guilherme A. S.; Pimenta, Luciano C. A.; Iscold, Paulo

2015-01-01

This paper presents a solution for the problem of minimum time coverage of ground areas using a group of unmanned air vehicles (UAVs) equipped with image sensors. The solution is divided into two parts: (i) the task modeling as a graph whose vertices are geographic coordinates determined in such a way that a single UAV would cover the area in minimum time; and (ii) the solution of a mixed integer linear programming problem, formulated according to the graph variables defined in the first part, to route the team of UAVs over the area. The main contribution of the proposed methodology, when compared with the traditional vehicle routing problem’s (VRP) solutions, is the fact that our method solves some practical problems only encountered during the execution of the task with actual UAVs. In this line, one of the main contributions of the paper is that the number of UAVs used to cover the area is automatically selected by solving the optimization problem. The number of UAVs is influenced by the vehicles’ maximum flight time and by the setup time, which is the time needed to prepare and launch a UAV. To illustrate the methodology, the paper presents experimental results obtained with two hand-launched, fixed-wing UAVs. PMID:26540055

Multi-UAV Routing for Area Coverage and Remote Sensing with Minimum Time.

PubMed

Avellar, Gustavo S C; Pereira, Guilherme A S; Pimenta, Luciano C A; Iscold, Paulo

2015-11-02

This paper presents a solution for the problem of minimum time coverage of ground areas using a group of unmanned air vehicles (UAVs) equipped with image sensors. The solution is divided into two parts: (i) the task modeling as a graph whose vertices are geographic coordinates determined in such a way that a single UAV would cover the area in minimum time; and (ii) the solution of a mixed integer linear programming problem, formulated according to the graph variables defined in the first part, to route the team of UAVs over the area. The main contribution of the proposed methodology, when compared with the traditional vehicle routing problem's (VRP) solutions, is the fact that our method solves some practical problems only encountered during the execution of the task with actual UAVs. In this line, one of the main contributions of the paper is that the number of UAVs used to cover the area is automatically selected by solving the optimization problem. The number of UAVs is influenced by the vehicles' maximum flight time and by the setup time, which is the time needed to prepare and launch a UAV. To illustrate the methodology, the paper presents experimental results obtained with two hand-launched, fixed-wing UAVs.

Mapping Gnss Restricted Environments with a Drone Tandem and Indirect Position Control

NASA Astrophysics Data System (ADS)

Cledat, E.; Cucci, D. A.

2017-08-01

The problem of autonomously mapping highly cluttered environments, such as urban and natural canyons, is intractable with the current UAV technology. The reason lies in the absence or unreliability of GNSS signals due to partial sky occlusion or multi-path effects. High quality carrier-phase observations are also required in efficient mapping paradigms, such as Assisted Aerial Triangulation, to achieve high ground accuracy without the need of dense networks of ground control points. In this work we consider a drone tandem in which the first drone flies outside the canyon, where GNSS constellation is ideal, visually tracks the second drone and provides an indirect position control for it. This enables both autonomous guidance and accurate mapping of GNSS restricted environments without the need of ground control points. We address the technical feasibility of this concept considering preliminary real-world experiments in comparable conditions and we perform a mapping accuracy prediction based on a simulation scenario.

Drones at the Beach - Surf Zone Monitoring Using Rotary Wing Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Rynne, P.; Brouwer, R.; de Schipper, M. A.; Graham, F.; Reniers, A.; MacMahan, J. H.

2014-12-01

We investigate the potential of rotary wing Unmanned Aerial Vehicles (UAVs) to monitor the surf zone. In recent years, the arrival of lightweight, high-capacity batteries, low-power electronics and compact high-definition cameras has driven the development of commercially available UAVs for hobbyists. Moreover, the low operation costs have increased their potential for scientific research as these UAVs are extremely flexible surveying platforms. The UAVs can fly for ~12 min with a mean loiter radius of 1 - 3.5 m and a mean loiter error of 0.75 - 4.5 m, depending on the environmental conditions, flying style, battery type and vehicle type. Our experiments using multiple, alternating UAVs show that it is possible to have near continuous imagery data with similar Fields Of View. The images obtained from the UAVs (Fig. 1a), and in combination with surveyed Ground Control Points (GCPs) (Fig. 1b, red squares and white circles), can be geo-rectified (Fig. 1c) to pixel resolution between 0.01 - 1 m and a reprojection error, i.e. the difference between the surveyed GPS location of a GCP and the location of the GCP obtained from the geo-rectified image, of O(1 m). These geo-rectified images provide data on a variety of coastal aspects, such as beach width (Wb(x,t)), surf zone width (Wsf(x,t)), wave breaking location (rectangle B), beach usage (circle C) and location of dune vegegation (rectangle D), amongst others. Additionally, the possibility to have consecutive, high frequency (up to 2 Hz) rectified images makes the UAVs a great data instrument for spatially and temporally variable systems, such as the surf zone. Our first observations with the UAVs reveal the potential to quickly obtain surf zone and beach characteristics in response to storms or for day to day beach information, as well as the scientific pursuits of surf zone kinematics on different spatial and temporal scales, and dispersion and advection estimates of pollutants/dye. A selection of findings from several field experiments and using multiple optical instruments will be showed at the meeting, discussing the new possibilities rotary wing UAVs can offer for surf zone research.

A Discussion of Aerodynamic Control Effectors (ACEs) for Unmanned Air Vehicles (UAVs)

NASA Technical Reports Server (NTRS)

Wood, Richard M.

2002-01-01

A Reynolds number based, unmanned air vehicle classification structure has been developed which identifies four classes of unmanned air vehicle concepts. The four unmanned air vehicle (UAV) classes are; Micro UAV, Meso UAV, Macro UAV, and Mega UAV. In a similar fashion a labeling scheme for aerodynamic control effectors (ACE) was developed and eleven types of ACE concepts were identified. These eleven types of ACEs were laid out in a five (5) layer scheme. The final section of the paper correlated the various ACE concepts to the four UAV classes and ACE recommendations are offered for future design activities.

Improved Seam-Line Searching Algorithm for UAV Image Mosaic with Optical Flow.

PubMed

Zhang, Weilong; Guo, Bingxuan; Li, Ming; Liao, Xuan; Li, Wenzhuo

2018-04-16

Ghosting and seams are two major challenges in creating unmanned aerial vehicle (UAV) image mosaic. In response to these problems, this paper proposes an improved method for UAV image seam-line searching. First, an image matching algorithm is used to extract and match the features of adjacent images, so that they can be transformed into the same coordinate system. Then, the gray scale difference, the gradient minimum, and the optical flow value of pixels in adjacent image overlapped area in a neighborhood are calculated, which can be applied to creating an energy function for seam-line searching. Based on that, an improved dynamic programming algorithm is proposed to search the optimal seam-lines to complete the UAV image mosaic. This algorithm adopts a more adaptive energy aggregation and traversal strategy, which can find a more ideal splicing path for adjacent UAV images and avoid the ground objects better. The experimental results show that the proposed method can effectively solve the problems of ghosting and seams in the panoramic UAV images.

Fault tolerant attitude sensing and force feedback control for unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Jagadish, Chirag

Two aspects of an unmanned aerial vehicle are studied in this work. One is fault tolerant attitude determination and the other is to provide force feedback to the joy-stick of the UAV so as to prevent faulty inputs from the pilot. Determination of attitude plays an important role in control of aerial vehicles. One way of defining the attitude is through Euler angles. These angles can be determined based on the measurements of the projections of the gravity and earth magnetic fields on the three body axes of the vehicle. Attitude determination in unmanned aerial vehicles poses additional challenges due to limitations of space, payload, power and cost. Therefore it provides for almost no room for any bulky sensors or extra sensor hardware for backup and as such leaves no room for sensor fault issues either. In the face of these limitations, this study proposes a fault tolerant computing of Euler angles by utilizing multiple different computation methods, with each method utilizing a different subset of the available sensor measurement data. Twenty-five such methods have been presented in this document. The capability of computing the Euler angles in multiple ways provides a diversified redundancy required for fault tolerance. The proposed approach can identify certain sets of sensor failures and even separate the reference fields from the disturbances. A bank-to-turn maneuver of the NASA GTM UAV is used to demonstrate the fault tolerance provided by the proposed method as well as to demonstrate the method of determining the correct Euler angles despite interferences by inertial acceleration disturbances. Attitude computation is essential for stability. But as of today most UAVs are commanded remotely by human pilots. While basic stability control is entrusted to machine or the on-board automatic controller, overall guidance is usually with humans. It is therefore the pilot who sets the command/references through a joy-stick. While this is a good compromise between complete automation and complete human control, it still poses some unique challenges. Pilots of manned aircraft are present inside the cockpit of the aircraft they fly and thus have a better feel of the flying environment and also the limitations of the flight. The same might not be true for UAV pilots stationed on the ground. A major handicap is that visual feedback is the only one available for the UAV pilot. An additional parameter like force feedback on the remote control joy-stick can help the UAV pilot to physically feel the limitation of the safe flight envelope. This can make the flying itself easier and safer. A method proposed here is to design a joy-stick assembly with an additional actuator. This actuator is controlled so as to generate a force feedback on the joy-stick. The control developed for this system is such that the actuator allows free movement for the pilot as long as the UAV is within the safe flight envelope. On the other hand, if it is outside this safe range, the actuator opposes the pilot's applied torque and prevents him/her from giving erroneous commands to the UAV.

a Micro-Uav with the Capability of Direct Georeferencing

NASA Astrophysics Data System (ADS)

Rehak, M.; Mabillard, R.; Skaloud, J.

2013-08-01

This paper presents the development of a low cost UAV (Unmanned Aerial Vehicle) with the capability of direct georeferencing. The advantage of such system lies in its high maneuverability, operation flexibility as well as capability to acquire image data without the need of establishing ground control points (GCPs). Moreover, the precise georeferencing offers an improvement in the final mapping accuracy when employing integrated sensor orientation. Such mode of operation limits the number and distribution of GCPs, which in turns save time in their signalization and surveying. Although the UAV systems feature high flexibility and capability of flying into areas that are inhospitable or inaccessible to humans, the lack of precision in positioning and attitude estimation on-board decrease the gained value of the captured imagery and limits their mode of operation to specific configurations and need of groundreference. Within a scope of this study we show the potential of present technologies in the field of position and orientation determination on a small UAV. The hardware implementation and especially the non-trivial synchronization of all components is clarified. Thanks to the implementation of a multi-frequency, low power GNSS receiver and its coupling with redundant MEMSIMU, we can attain the characteristic of a much larger systems flown on large carries while keeping the sensor size and weight suitable for MAV operations.

UAV formation control design with obstacle avoidance in dynamic three-dimensional environment.

PubMed

Chang, Kai; Xia, Yuanqing; Huang, Kaoli

2016-01-01

This paper considers the artificial potential field method combined with rotational vectors for a general problem of multi-unmanned aerial vehicle (UAV) systems tracking a moving target in dynamic three-dimensional environment. An attractive potential field is generated between the leader and the target. It drives the leader to track the target based on the relative position of them. The other UAVs in the formation are controlled to follow the leader by the attractive control force. The repulsive force affects among the UAVs to avoid collisions and distribute the UAVs evenly on the spherical surface whose center is the leader-UAV. Specific orders or positions of the UAVs are not required. The trajectories of avoidance obstacle can be obtained through two kinds of potential field with rotation vectors. Every UAV can choose the optimal trajectory to avoid the obstacle and reconfigure the formation after passing the obstacle. Simulations study on UAV are presented to demonstrate the effectiveness of proposed method.

Vegetation Removal from Uav Derived Dsms, Using Combination of RGB and NIR Imagery

NASA Astrophysics Data System (ADS)

Skarlatos, D.; Vlachos, M.

2018-05-01

Current advancements on photogrammetric software along with affordability and wide spreading of Unmanned Aerial Vehicles (UAV), allow for rapid, timely and accurate 3D modelling and mapping of small to medium sized areas. Although the importance and applications of large format aerial overlaps cameras and photographs in Digital Surface Model (DSM) production and LIDAR data is well documented in literature, this is not the case for UAV photography. Additionally, the main disadvantage of photogrammetry is the inability to map the dead ground (terrain), when we deal with areas that include vegetation. This paper assesses the use of near-infrared imagery captured by small UAV platforms to automatically remove vegetation from Digital Surface Models (DSMs) and obtain a Digital Terrain Model (DTM). Two areas were tested, based on the availability of ground reference points, both under trees and among vegetation, as well as on terrain. In addition, RGB and near-infrared UAV photography was captured and processed using Structure from Motion (SfM) and Multi View Stereo (MVS) algorithms to generate DSMs and corresponding colour and NIR orthoimages with 0.2 m and 0.25 m as pixel size respectively for the two test sites. Moreover, orthophotos were used to eliminate the vegetation from the DSMs using NDVI index, thresholding and masking. Following that, different interpolation algorithms, according to the test sites, were applied to fill in the gaps and created DTMs. Finally, a statistic analysis was made using reference terrain points captured on field, both on dead ground and under vegetation to evaluate the accuracy of the whole process and assess the overall accuracy of the derived DTMs in contrast with the DSMs.

Tactical UAV’s in the French Army

DTIC Science & Technology

2003-09-02

French Army Technical Service, France 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR... FRENCH ARMY PROJECTION PLATOON Platoon Maintenance Facilities (1st & 2nd echelons) Platoon HQ Launching System Ground Control Station / Remote Data...Tactical UAV’s in the French Army LtCol Pierre-Yves HENRY, Technical Service of the French Army, Program Officer for Battlefield Surveillance Report

Designing Unmanned Systems with Greater Autonomy: Using a Federated, Partially Open Systems Architecture Approach

DTIC Science & Technology

2014-01-01

system UAV unmanned aircraft vehicle UCI User -Computer Interface UCS UAS control segment Abbreviations xxix UGS unmanned ground system UGV unmanned ...made substantial progress in the deployment of more capable sensors, unmanned aircraft systems (UAS), and other unmanned systems (UxS). Innovative...progress in fielding more, and more capable unmanned aircraft systems (UAS) to meet the needs of warfighters

UAV-based landslide deformation monitoring - first results from Corvara landslide

NASA Astrophysics Data System (ADS)

Thiebes, Benni; Tomelleri, Enrico; Mejia-Aguilar, Abraham; Schlögel, Romy; Darvishi, Mehdi; Remondino, Fabio; Toschi, Isabella; Rutzinger, Martin; Zieher, Thomas

2016-04-01

In recent years, unmanned aerial vehicles (UAVs) have been more frequently utilised to study geomorphological and natural hazard processes, including gravitational mass movements such as landslides. UAVs can be equipped with different sensors, e.g. photo cameras and laser scanners, and the data that can be achieved can substantially improve the monitoring and understanding of the involved natural processes. One of the main advantages of UAVs is their flexibility that allows for carrying out assessments of large areas in short periods of time and at much lower costs than other platforms, e.g. airplanes or helicopters. Thereby, UAVs represent an interesting technique to complement more traditional monitoring methods. Here we present some first results of the EUREGIO-funded LEMONADE project that is concerned with the combination and integration of novel and traditional landslide monitoring techniques. We carried out a series of UAV flights over a particularly active part of the Corvara landslide and acquired aerial imagery for quantitative assessments of the retrogressive enlargement of the landslide over recent years. Additional field surveys including terrestrial laser scanning, and UAV-based photogrammetry and laser scanning are scheduled for summer 2016. The Corvara landslide is a large complex earthflow in the Italian Dolomites that has been investigated by a wide range of methodologies over the past years. The landslide is characterised by movement patterns of greatly varying magnitude, ranging from annual rates of a few cm to more than 20 m. The current and past monitoring activities concentrated on GPS measurements as well as multi-temporal differential radar interferometry utilising artificial corner reflectors. Thereby, primarily punctual displacement data were achieved and spatial information on topographic and geomorphic changes were consequently sparse. For our photogrammetry study, we utilised a SoLeon octocopter equipped with a Ricoh GR 16.2 Megapixels camera. Three photos were taken with different exposure settings every 2 seconds while the UAV followed a pre-programmed flight track in an elevation of 70 m above ground and a flight speed of 1 m/s. Ground-control points were distributed to allow for reliable merging as well as for georeferencing of the resulting imagery. Within one day, approximately 13 ha were covered with an orthophoto and point cloud of extremely high spatial resolution. The point cloud consisting of more than 200 million points was transferred to a digital surface model (DSM) with 1.5 cm resolution, and was subsequently compared to the 2006 LiDAR based DSM. The comparison of the results highlights areas of vertical topographic changes which reached up to 12 m. Moreover, the retrogressive enlargement of the landslide could be quantified and partly exceeds 30 m within the past 4 years only.

UAV photogrammetry for topographic monitoring of coastal areas

NASA Astrophysics Data System (ADS)

Gonçalves, J. A.; Henriques, R.

2015-06-01

Coastal areas suffer degradation due to the action of the sea and other natural and human-induced causes. Topographical changes in beaches and sand dunes need to be assessed, both after severe events and on a regular basis, to build models that can predict the evolution of these natural environments. This is an important application for airborne LIDAR, and conventional photogrammetry is also being used for regular monitoring programs of sensitive coastal areas. This paper analyses the use of unmanned aerial vehicles (UAV) to map and monitor sand dunes and beaches. A very light plane (SwingletCam) equipped with a very cheap, non-metric camera was used to acquire images with ground resolutions better than 5 cm. The Agisoft Photoscan software was used to orientate the images, extract point clouds, build a digital surface model and produce orthoimage mosaics. The processing, which includes automatic aerial triangulation with camera calibration and subsequent model generation, was mostly automated. To achieve the best positional accuracy for the whole process, signalised ground control points were surveyed with a differential GPS receiver. Two very sensitive test areas on the Portuguese northwest coast were analysed. Detailed DSMs were obtained with 10 cm grid spacing and vertical accuracy (RMS) ranging from 3.5 to 5.0 cm, which is very similar to the image ground resolution (3.2-4.5 cm). Where possible to assess, the planimetric accuracy of the orthoimage mosaics was found to be subpixel. Within the regular coastal monitoring programme being carried out in the region, UAVs can replace many of the conventional flights, with considerable gains in the cost of the data acquisition and without any loss in the quality of topographic and aerial imagery data.

Efficiency calibration and minimum detectable activity concentration of a real-time UAV airborne sensor system with two gamma spectrometers.

PubMed

Tang, Xiao-Bin; Meng, Jia; Wang, Peng; Cao, Ye; Huang, Xi; Wen, Liang-Sheng; Chen, Da

2016-04-01

A small-sized UAV (NH-UAV) airborne system with two gamma spectrometers (LaBr3 detector and HPGe detector) was developed to monitor activity concentration in serious nuclear accidents, such as the Fukushima nuclear accident. The efficiency calibration and determination of minimum detectable activity concentration (MDAC) of the specific system were studied by MC simulations at different flight altitudes, different horizontal distances from the detection position to the source term center and different source term sizes. Both air and ground radiation were considered in the models. The results obtained may provide instructive suggestions for in-situ radioactivity measurements of NH-UAV. Copyright © 2016 Elsevier Ltd. All rights reserved.

Quality of terrestrial data derived from UAV photogrammetry: a case study of the Hetao irrigation district in northern China

NASA Astrophysics Data System (ADS)

Zhang, Hongming; Baartman, Jantiene E. M.; Yang, Xiaomei; Gai, Lingtong; Geissen, Violette

2017-04-01

Most crops in northern China are irrigated, but the topography affects water use, soil erosion, runoff and yields,. Technologies for collecting high-resolution topographic data are essential for adequately assessing these effects. Ground surveys and techniques of light detection and ranging have good accuracy, but data acquisition can be time-consuming and expensive for large catchments. Recent rapid technological development has provided new, flexible, high-resolution methods for collecting topographic data, such as photogrammetry using unmanned aerial vehicles (UAVs). The accuracy of UAV photogrammetry for generating high-resolution digital elevation models (DEMs) and for determining the width of irrigation channels, however, has not been assessed. We used a fixed-wing UAV for collecting high-resolution (0.15 m) topographic data for the Hetao irrigation district, the third largest irrigation district in China. We surveyed 112 ground checkpoints (GCPs) using a real-time kinematic global positioning system to evaluate the accuracy of the DEMs and channel widths. A comparison of manually measured channel widths with the widths derived from the DEMs indicated that the DEM-derived widths had vertical and horizontal root mean square errors of 13.0 and 7.9 cm, respectively. UAV photogrammetric data can thus be used for land surveying, digital mapping, calculating channel capacity, monitoring crops, and predicting yields, with the advantages of economy, speed, and ease.

The Combination of Uav Survey and Landsat Imagery for Monitoring of Crop Vigor in Precision Agriculture

NASA Astrophysics Data System (ADS)

Lukas, V.; Novák, J.; Neudert, L.; Svobodova, I.; Rodriguez-Moreno, F.; Edrees, M.; Kren, J.

2016-06-01

Mapping of the with-in field variability of crop vigor has a long tradition with a success rate ranging from medium to high depending on the local conditions of the study. Information about the development of agronomical relevant crop parameters, such as above-ground biomass and crop nutritional status, provides high reliability for yield estimation and recommendation for variable rate application of fertilizers. The aim of this study was to utilize unmanned and satellite multispectral imaging for estimation of basic crop parameters during the growing season. The experimental part of work was carried out in 2014 at the winter wheat field with an area of 69 ha located in the South Moravia region of the Czech Republic. An UAV imaging was done in April 2014 using Sensefly eBee, which was equipped by visible and near infrared (red edge) multispectral cameras. For ground truth calibration the spectral signatures were measured on 20 sites using portable spectroradiometer ASD Handheld 2 and simultaneously plant samples were taken at BBCH 32 (April 2014) and BBCH 59 (Mai 2014) for estimation of above-ground biomass and nitrogen content. The UAV survey was later extended by selected cloud-free Landsat 8 OLI satellite imagery, downloaded from USGS web application Earth Explorer. After standard pre-processing procedures, a set of vegetation indices was calculated from remotely and ground sensed data. As the next step, a correlation analysis was computed among crop vigor parameters and vegetation indices. Both, amount of above-ground biomass and nitrogen content were highly correlated (r > 0.85) with ground spectrometric measurement by ASD Handheld 2 in BBCH 32, especially for narrow band vegetation indices (e.g. Red Edge Inflection Point). UAV and Landsat broadband vegetation indices varied in range of r = 0.5 - 0.7, highest values of the correlation coefficients were obtained for crop biomass by using GNDVI. In all cases results from BBCH 59 vegetation stage showed lower relationship to vegetation indices. Total amount of aboveground biomass was identified as the most important factor influencing the values of vegetation indices. Based on the results can be assumed that UAV and satellite monitoring provide reliable information about crop parameters for site specific crop management. The main difference of their utilization is coming from their specification and technical limits. Satellite survey can be used for periodic monitoring of crops as the indicator of their spatial heterogeneity within fields, but with low resolution (30 m per pixel for OLI). On the other hand UAV represents a special campaign aimed on the mapping of high-detailed spatial inputs for site specific crop management and variable rate application of fertilizers.

An Autonomous Autopilot Control System Design for Small-Scale UAVs

NASA Technical Reports Server (NTRS)

Ippolito, Corey; Pai, Ganeshmadhav J.; Denney, Ewen W.

2012-01-01

This paper describes the design and implementation of a fully autonomous and programmable autopilot system for small scale autonomous unmanned aerial vehicle (UAV) aircraft. This system was implemented in Reflection and has flown on the Exploration Aerial Vehicle (EAV) platform at NASA Ames Research Center, currently only as a safety backup for an experimental autopilot. The EAV and ground station are built on a component-based architecture called the Reflection Architecture. The Reflection Architecture is a prototype for a real-time embedded plug-and-play avionics system architecture which provides a transport layer for real-time communications between hardware and software components, allowing each component to focus solely on its implementation. The autopilot module described here, although developed in Reflection, contains no design elements dependent on this architecture.

Smart Camera System for Aircraft and Spacecraft

NASA Technical Reports Server (NTRS)

Delgado, Frank; White, Janis; Abernathy, Michael F.

2003-01-01

This paper describes a new approach to situation awareness that combines video sensor technology and synthetic vision technology in a unique fashion to create a hybrid vision system. Our implementation of the technology, called "SmartCam3D" (SC3D) has been flight tested by both NASA and the Department of Defense with excellent results. This paper details its development and flight test results. Windshields and windows add considerable weight and risk to vehicle design, and because of this, many future vehicles will employ a windowless cockpit design. This windowless cockpit design philosophy prompted us to look at what would be required to develop a system that provides crewmembers and awareness. The system created to date provides a real-time operations personnel an appropriate level of situation 3D perspective display that can be used during all-weather and visibility conditions. While the advantages of a synthetic vision only system are considerable, the major disadvantage of such a system is that it displays the synthetic scene created using "static" data acquired by an aircraft or satellite at some point in the past. The SC3D system we are presenting in this paper is a hybrid synthetic vision system that fuses live video stream information with a computer generated synthetic scene. This hybrid system can display a dynamic, real-time scene of a region of interest, enriched by information from a synthetic environment system, see figure 1. The SC3D system has been flight tested on several X-38 flight tests performed over the last several years and on an ARMY Unmanned Aerial Vehicle (UAV) ground control station earlier this year. Additional testing using an assortment of UAV ground control stations and UAV simulators from the Army and Air Force will be conducted later this year.

Output feedback control of a quadrotor UAV using neural networks.

PubMed

Dierks, Travis; Jagannathan, Sarangapani

2010-01-01

In this paper, a new nonlinear controller for a quadrotor unmanned aerial vehicle (UAV) is proposed using neural networks (NNs) and output feedback. The assumption on the availability of UAV dynamics is not always practical, especially in an outdoor environment. Therefore, in this work, an NN is introduced to learn the complete dynamics of the UAV online, including uncertain nonlinear terms like aerodynamic friction and blade flapping. Although a quadrotor UAV is underactuated, a novel NN virtual control input scheme is proposed which allows all six degrees of freedom (DOF) of the UAV to be controlled using only four control inputs. Furthermore, an NN observer is introduced to estimate the translational and angular velocities of the UAV, and an output feedback control law is developed in which only the position and the attitude of the UAV are considered measurable. It is shown using Lyapunov theory that the position, orientation, and velocity tracking errors, the virtual control and observer estimation errors, and the NN weight estimation errors for each NN are all semiglobally uniformly ultimately bounded (SGUUB) in the presence of bounded disturbances and NN functional reconstruction errors while simultaneously relaxing the separation principle. The effectiveness of proposed output feedback control scheme is then demonstrated in the presence of unknown nonlinear dynamics and disturbances, and simulation results are included to demonstrate the theoretical conjecture.

Bio-inspired UAV routing, source localization, and acoustic signature classification for persistent surveillance

NASA Astrophysics Data System (ADS)

Burman, Jerry; Hespanha, Joao; Madhow, Upamanyu; Pham, Tien

2011-06-01

A team consisting of Teledyne Scientific Company, the University of California at Santa Barbara and the Army Research Laboratory* is developing technologies in support of automated data exfiltration from heterogeneous battlefield sensor networks to enhance situational awareness for dismounts and command echelons. Unmanned aerial vehicles (UAV) provide an effective means to autonomously collect data from a sparse network of unattended ground sensors (UGSs) that cannot communicate with each other. UAVs are used to reduce the system reaction time by generating autonomous collection routes that are data-driven. Bio-inspired techniques for search provide a novel strategy to detect, capture and fuse data. A fast and accurate method has been developed to localize an event by fusing data from a sparse number of UGSs. This technique uses a bio-inspired algorithm based on chemotaxis or the motion of bacteria seeking nutrients in their environment. A unique acoustic event classification algorithm was also developed based on using swarm optimization. Additional studies addressed the problem of routing multiple UAVs, optimally placing sensors in the field and locating the source of gunfire at helicopters. A field test was conducted in November of 2009 at Camp Roberts, CA. The field test results showed that a system controlled by bio-inspired software algorithms can autonomously detect and locate the source of an acoustic event with very high accuracy and visually verify the event. In nine independent test runs of a UAV, the system autonomously located the position of an explosion nine times with an average accuracy of 3 meters. The time required to perform source localization using the UAV was on the order of a few minutes based on UAV flight times. In June 2011, additional field tests of the system will be performed and will include multiple acoustic events, optimal sensor placement based on acoustic phenomenology and the use of the International Technology Alliance (ITA) Sensor Network Fabric (IBM).

Data Acquisition (DAQ) system dedicated for remote sensing applications on Unmanned Aerial Vehicles (UAV)

NASA Astrophysics Data System (ADS)

Keleshis, C.; Ioannou, S.; Vrekoussis, M.; Levin, Z.; Lange, M. A.

2014-08-01

Continuous advances in unmanned aerial vehicles (UAV) and the increased complexity of their applications raise the demand for improved data acquisition systems (DAQ). These improvements may comprise low power consumption, low volume and weight, robustness, modularity and capability to interface with various sensors and peripherals while maintaining the high sampling rates and processing speeds. Such a system has been designed and developed and is currently integrated on the Autonomous Flying Platforms for Atmospheric and Earth Surface Observations (APAESO/NEA-YΠOΔOMH/NEKΠ/0308/09) however, it can be easily adapted to any UAV or any other mobile vehicle. The system consists of a single-board computer with a dual-core processor, rugged surface-mount memory and storage device, analog and digital input-output ports and many other peripherals that enhance its connectivity with various sensors, imagers and on-board devices. The system is powered by a high efficiency power supply board. Additional boards such as frame-grabbers, differential global positioning system (DGPS) satellite receivers, general packet radio service (3G-4G-GPRS) modems for communication redundancy have been interfaced to the core system and are used whenever there is a mission need. The onboard DAQ system can be preprogrammed for automatic data acquisition or it can be remotely operated during the flight from the ground control station (GCS) using a graphical user interface (GUI) which has been developed and will also be presented in this paper. The unique design of the GUI and the DAQ system enables the synchronized acquisition of a variety of scientific and UAV flight data in a single core location. The new DAQ system and the GUI have been successfully utilized in several scientific UAV missions. In conclusion, the novel DAQ system provides the UAV and the remote-sensing community with a new tool capable of reliably acquiring, processing, storing and transmitting data from any sensor integrated on an UAV.

Distributed pheromone-based swarming control of unmanned air and ground vehicles for RSTA

NASA Astrophysics Data System (ADS)

Sauter, John A.; Mathews, Robert S.; Yinger, Andrew; Robinson, Joshua S.; Moody, John; Riddle, Stephanie

2008-04-01

The use of unmanned vehicles in Reconnaissance, Surveillance, and Target Acquisition (RSTA) applications has received considerable attention recently. Cooperating land and air vehicles can support multiple sensor modalities providing pervasive and ubiquitous broad area sensor coverage. However coordination of multiple air and land vehicles serving different mission objectives in a dynamic and complex environment is a challenging problem. Swarm intelligence algorithms, inspired by the mechanisms used in natural systems to coordinate the activities of many entities provide a promising alternative to traditional command and control approaches. This paper describes recent advances in a fully distributed digital pheromone algorithm that has demonstrated its effectiveness in managing the complexity of swarming unmanned systems. The results of a recent demonstration at NASA's Wallops Island of multiple Aerosonde Unmanned Air Vehicles (UAVs) and Pioneer Unmanned Ground Vehicles (UGVs) cooperating in a coordinated RSTA application are discussed. The vehicles were autonomously controlled by the onboard digital pheromone responding to the needs of the automatic target recognition algorithms. UAVs and UGVs controlled by the same pheromone algorithm self-organized to perform total area surveillance, automatic target detection, sensor cueing, and automatic target recognition with no central processing or control and minimal operator input. Complete autonomy adds several safety and fault tolerance requirements which were integrated into the basic pheromone framework. The adaptive algorithms demonstrated the ability to handle some unplanned hardware failures during the demonstration without any human intervention. The paper describes lessons learned and the next steps for this promising technology.

UAV magnetometry in mineral exploration and infrastructure detection

NASA Astrophysics Data System (ADS)

Braun, A.; Parvar, K.; Burns, M.

2015-12-01

Magnetic surveys are critical tools in mineral exploration and UAVs have the potential to carry magnetometers. UAV surveys can offer higher spatial resolution than traditional airborne surveys, and higher coverage than terrestrial surveys. However, the main advantage is their ability to sense the magnetic field in 3-D, while most airborne or terrestrial surveys are restricted to 2-D acquisition. This study compares UAV magnetic data from two different UAVs (JIB drone, DJI Phantom 2) and three different magnetometers (GEM GSPM35, Honeywell HMR2300, GEM GST-19). The first UAV survey was conducted using a JIB UAV with a GSPM35 flying at 10-15 m above ground. The survey's goal was to detect intrusive Rhyolite bodies for primary mineral exploration. The survey resulted in a better understanding of the validity/resolution of UAV data and led to improved knowledge about the geological structures in the area. The results further drove the design of a following terrestrial survey. Comparing the UAV data with an available airborne survey (upward continued to 250 m) reveals that the UAV data has superior spatial resolution, but exhibits a higher noise level. The magnetic anomalies related to the Rhyolite intrusions is about 109 nT and translates into an estimated depth of approximately 110 meters. The second survey was conducted using an in-house developed UAV magnetometer system equipped with a DJI Phantom 2 and a Honeywell HMR2300 fluxgate magnetometer. By flying the sensor in different altitudes, the vertical and horizontal gradients can be derived leading to full 3-D magnetic data volumes which can provide improved constraints for source depth/geometry characterization. We demonstrate that a buried steam pipeline was detectable with the UAV magnetometer system and compare the resulting data with a terrestrial survey using a GEM GST-19 Proton Precession Magnetometer.

DTM Generation Through Uav Survey with a Fisheye Camera on a Vineyard

NASA Astrophysics Data System (ADS)

Ronchetti, G.; Pagliari, D.; Sona, G.

2018-05-01

Precision agriculture recommends a sustainable employment of nutrients and water, according to the site-specific crop requirements. In this context, the knowledge of soil characteristics allows to appropriately manage resources. Even the topography can influence the spatial distribution of the water on a field. This work focuses on the production of high-resolution Digital Terrain Model (DTM) in agriculture by photogrammetric processing fisheye images, acquired with very light Unmanned Aerial Vehicle (UAV). Particular attention is given to the data processing procedures and to the assessment of the quality of the results, considering the peculiarity of the acquired images. An experimental test has been carried out on a vineyard located in Monzambano, Northern Italy, through photogrammetric survey with Parrot Bebop 2 UAV. It has been realized at the end of the vegetation season, to investigate the ground without any impediment due to the presence of leaves or branches. In addition, the survey has been used for evaluating the performance of Bebop fisheye camera in viticulture. Different flight strategies have been tested, together with different Ground Control Points (GCPs) and Check Points (CPs) configurations and software packages. The computed DTMs have been compared with a reference model obtained through Kriging interpolation of GNSS-RTK measurements. Residuals on CPs are of the order of 0.06 m, for all the considered scenarios, that for agricultural applications is by far sufficient. The photogrammetric DTMs show a good agreement with the reference one.

Integrated long-range UAV/UGV collaborative target tracking

NASA Astrophysics Data System (ADS)

Moseley, Mark B.; Grocholsky, Benjamin P.; Cheung, Carol; Singh, Sanjiv

2009-05-01

Coordinated operations between unmanned air and ground assets allow leveraging of multi-domain sensing and increase opportunities for improving line of sight communications. While numerous military missions would benefit from coordinated UAV-UGV operations, foundational capabilities that integrate stove-piped tactical systems and share available sensor data are required and not yet available. iRobot, AeroVironment, and Carnegie Mellon University are working together, partially SBIR-funded through ARDEC's small unit network lethality initiative, to develop collaborative capabilities for surveillance, targeting, and improved communications based on PackBot UGV and Raven UAV platforms. We integrate newly available technologies into computational, vision, and communications payloads and develop sensing algorithms to support vision-based target tracking. We first simulated and then applied onto real tactical platforms an implementation of Decentralized Data Fusion, a novel technique for fusing track estimates from PackBot and Raven platforms for a moving target in an open environment. In addition, system integration with AeroVironment's Digital Data Link onto both air and ground platforms has extended our capabilities in communications range to operate the PackBot as well as in increased video and data throughput. The system is brought together through a unified Operator Control Unit (OCU) for the PackBot and Raven that provides simultaneous waypoint navigation and traditional teleoperation. We also present several recent capability accomplishments toward PackBot-Raven coordinated operations, including single OCU display design and operation, early target track results, and Digital Data Link integration efforts, as well as our near-term capability goals.

An accelerated image matching technique for UAV orthoimage registration

NASA Astrophysics Data System (ADS)

Tsai, Chung-Hsien; Lin, Yu-Ching

2017-06-01

Using an Unmanned Aerial Vehicle (UAV) drone with an attached non-metric camera has become a popular low-cost approach for collecting geospatial data. A well-georeferenced orthoimage is a fundamental product for geomatics professionals. To achieve high positioning accuracy of orthoimages, precise sensor position and orientation data, or a number of ground control points (GCPs), are often required. Alternatively, image registration is a solution for improving the accuracy of a UAV orthoimage, as long as a historical reference image is available. This study proposes a registration scheme, including an Accelerated Binary Robust Invariant Scalable Keypoints (ABRISK) algorithm and spatial analysis of corresponding control points for image registration. To determine a match between two input images, feature descriptors from one image are compared with those from another image. A "Sorting Ring" is used to filter out uncorrected feature pairs as early as possible in the stage of matching feature points, to speed up the matching process. The results demonstrate that the proposed ABRISK approach outperforms the vector-based Scale Invariant Feature Transform (SIFT) approach where radiometric variations exist. ABRISK is 19.2 times and 312 times faster than SIFT for image sizes of 1000 × 1000 pixels and 4000 × 4000 pixels, respectively. ABRISK is 4.7 times faster than Binary Robust Invariant Scalable Keypoints (BRISK). Furthermore, the positional accuracy of the UAV orthoimage after applying the proposed image registration scheme is improved by an average of root mean square error (RMSE) of 2.58 m for six test orthoimages whose spatial resolutions vary from 6.7 cm to 10.7 cm.

High-Altitude, Long-Endurance UAVs vs. Satellites: Potential Benefits for U.S. Army Applications

DTIC Science & Technology

2009-05-01

Refractive Imaging System ....... Point Spread Function ......................... Transmission Characteristics of the Earth’s Atmosphere ...... Scanning...Angle in degrees Commwt Communications Payload Weight p Angular Radius of the Earth in degrees Palbedo Earth’s Albedo Patm Atmospheric Density in...femto-watt (10-15) FY Fiscal Year Gbps Gigabits per Second GBS Global Broadcast System GCS Ground Control Station GEO Geosynchronous Earth Orbit

Proceedings for the Advance Planning Briefing for Industry

DTIC Science & Technology

1990-01-24

Liaison Office TOD - Technical Objective Documents TSR - Tactical Source Region UAV - Unmanned Aerial Vehicle UGT - UnderGround nuclear Test A G.EN D635I...tests in AURORA and underground nuclear tests ( UGT ) and will help develop tactical source region hardening requirements and lead to approaches for TSR...X-Ray theory , lasers, electronic controllers, computers, robotics, etc. Contracting for scientific studies and one-of-a-kind machines will emphasize

Improved Seam-Line Searching Algorithm for UAV Image Mosaic with Optical Flow

PubMed Central

Zhang, Weilong; Guo, Bingxuan; Liao, Xuan; Li, Wenzhuo

2018-01-01

Ghosting and seams are two major challenges in creating unmanned aerial vehicle (UAV) image mosaic. In response to these problems, this paper proposes an improved method for UAV image seam-line searching. First, an image matching algorithm is used to extract and match the features of adjacent images, so that they can be transformed into the same coordinate system. Then, the gray scale difference, the gradient minimum, and the optical flow value of pixels in adjacent image overlapped area in a neighborhood are calculated, which can be applied to creating an energy function for seam-line searching. Based on that, an improved dynamic programming algorithm is proposed to search the optimal seam-lines to complete the UAV image mosaic. This algorithm adopts a more adaptive energy aggregation and traversal strategy, which can find a more ideal splicing path for adjacent UAV images and avoid the ground objects better. The experimental results show that the proposed method can effectively solve the problems of ghosting and seams in the panoramic UAV images. PMID:29659526

Autonomous Control of a Quadrotor UAV Using Fuzzy Logic

NASA Astrophysics Data System (ADS)

Sureshkumar, Vijaykumar

UAVs are being increasingly used today than ever before in both military and civil applications. They are heavily preferred in "dull, dirty or dangerous" mission scenarios. Increasingly, UAVs of all kinds are being used in policing, fire-fighting, inspection of structures, pipelines etc. Recently, the FAA gave its permission for UAVs to be used on film sets for motion capture and high definition video recording. The rapid development in MEMS and actuator technology has made possible a plethora of UAVs that are suited for commercial applications in an increasingly cost effective manner. An emerging popular rotary wing UAV platform is the Quadrotor A Quadrotor is a helicopter with four rotors, that make it more stable; but more complex to model and control. Characteristics that provide a clear advantage over other fixed wing UAVs are VTOL and hovering capabilities as well as a greater maneuverability. It is also simple in construction and design compared to a scaled single rotorcraft. Flying such UAVs using a traditional radio Transmitter-Receiver setup can be a daunting task especially in high stress situations. In order to make such platforms widely applicable, a certain level of autonomy is imperative to the future of such UAVs. This thesis paper presents a methodology for the autonomous control of a Quadrotor UAV using Fuzzy Logic. Fuzzy logic control has been chosen over conventional control methods as it can deal effectively with highly nonlinear systems, allows for imprecise data and is extremely modular. Modularity and adaptability are the key cornerstones of FLC. The objective of this thesis is to present the steps of designing, building and simulating an intelligent flight control module for a Quadrotor UAV. In the course of this research effort, a Quadrotor UAV is indigenously developed utilizing the resources of an online open source project called Aeroquad. System design is comprehensively dealt with. A math model for the Quadrotor is developed and a simulation environment is built in the MATLAB/Simulink framework. The Fuzzy flight controller development is discussed intensively. Validation of the math model developed is presented using actual flight data. Excellent attitude tracking is demonstrated for near hover flight regimes. The responses are analyzed and future work involving implementation is discussed.

Radar sensing via a Micro-UAV-borne system

NASA Astrophysics Data System (ADS)

Catapano, Ilaria; Ludeno, Giovanni; Gennarelli, Gianluca; Soldovieri, Francesco; Rodi Vetrella, Amedeo; Fasano, Giancarmine

2017-04-01

In recent years, the miniaturization of flight control systems and payloads has contributed to a fast and widespread diffusion of micro-UAV (Unmanned Aircraft Vehicle). While micro-UAV can be a powerful tool in several civil applications such as environmental monitoring and surveillance, unleashing their full potential for societal benefits requires augmenting their sensing capability beyond the realm of active/passive optical sensors [1]. In this frame, radar systems are drawing attention since they allow performing missions in all-weather and day/night conditions and, thanks to the microwave ability to penetrate opaque media, they enable the detection and localization not only of surface objects but also of sub-surface/hidden targets. However, micro-UAV-borne radar imaging represents still a new frontier, since it is much more than a matter of technology miniaturization or payload installation, which can take advantage of the newly developed ultralight systems. Indeed, micro-UAV-borne radar imaging entails scientific challenges in terms of electromagnetic modeling and knowledge of flight dynamics and control. As a consequence, despite Synthetic Aperture Radar (SAR) imaging is a traditional remote sensing tool, its adaptation to micro-UAV is an open issue and so far only few case studies concerning the integration of SAR and UAV technologies have been reported worldwide [2]. In addition, only early results concerning subsurface imaging by means of an UAV-mounted radar are available [3]. As a contribution to radar imaging via autonomous micro-UAV, this communication presents a proof-of-concept experiment. This experiment represents the first step towards the development of a general methodological approach that exploits expertise about (sub-)surface imaging and aerospace systems with the aim to provide high-resolution images of the surveyed scene. In details, at the conference, we will present the results of a flight campaign carried out by using a single radar-equipped drone. The system is made by a commercial radar system, whose mass, size, power and cost budgets is compatible with the installation on micro-UAV. The radar system has been mounted on a DJI 550 UAV, a flexible hexacopter allowing both complex flight operations and static flight, and has been equipped with small size log-periodic antennas, having a 6 dB gain over the frequency range from 2 GHz to 11 GHz. An ad-hoc signal processing chain has been adopted to process the collected raw data and obtain an image of the investigated scenario providing an accurate target detection and localization. This chain involves a SVD-based noise filter procedure and an advanced data processing approach, which assumes a linear model of the underlying scattering phenomenon. REFERENCES [1] K. Whitehead, C. H. Hugenholtz, "Remote sensing of the environment with small unmanned aircraft systems (UASs), part 1: a review of progress and challenges", J. Unmanned Vehicle Systems, vol.2, pp. 69-85, 2014. [2] K. Ouchi, Recent trend and advance of synthetic aperture radar with selected topics, Remote Sens, vol.5, pp.716-807, 2013. [3] D. Altdor et al., UAV-borne electromagnetic induction and ground-penetrating radar measurements: a feasibility test, 74th Annual Meeting of the Deutsche Geophysikalische Gesellschaft in Karlsruhe, Germany, March 9 - 13, 2014.

Distributed control systems with incomplete and uncertain information

NASA Astrophysics Data System (ADS)

Tang, Jingpeng

Scientific and engineering advances in wireless communication, sensors, propulsion, and other areas are rapidly making it possible to develop unmanned air vehicles (UAVs) with sophisticated capabilities. UAVs have come to the forefront as tools for airborne reconnaissance to search for, detect, and destroy enemy targets in relatively complex environments. They potentially reduce risk to human life, are cost effective, and are superior to manned aircraft for certain types of missions. It is desirable for UAVs to have a high level of intelligent autonomy to carry out mission tasks with little external supervision and control. This raises important issues involving tradeoffs between centralized control and the associated potential to optimize mission plans, and decentralized control with great robustness and the potential to adapt to changing conditions. UAV capabilities have been extended several ways through armament (e.g., Hellfire missiles on Predator UAVs), increased endurance and altitude (e.g., Global Hawk), and greater autonomy. Some known barriers to full-scale implementation of UAVs are increased communication and control requirements as well as increased platform and system complexity. One of the key problems is how UAV systems can handle incomplete and uncertain information in dynamic environments. Especially when the system is composed of heterogeneous and distributed UAVs, the overall system complexity is increased under such conditions. Presented through the use of published papers, this dissertation lays the groundwork for the study of methodologies for handling incomplete and uncertain information for distributed control systems. An agent-based simulation framework is built to investigate mathematical approaches (optimization) and emergent intelligence approaches. The first paper provides a mathematical approach for systems of UAVs to handle incomplete and uncertain information. The second paper describes an emergent intelligence approach for UAVs, again in handling incomplete and uncertain information. The third paper combines mathematical and emergent intelligence approaches.

Coastal areas mapping using UAV photogrammetry

NASA Astrophysics Data System (ADS)

Nikolakopoulos, Konstantinos G.; Kozarski, Dimitrios; Kogkas, Stefanos

2017-10-01

The coastal areas in the Patras Gulf suffer degradation due to the sea action and other natural and human-induced causes. Changes in beaches, ports, and other man made constructions need to be assessed, both after severe events and on a regular basis, to build models that can predict the evolution in the future. Thus, reliable spatial data acquisition is a critical process for the identification of the coastline and the broader coastal zones for geologists and other scientists involved in the study of coastal morphology. High resolution satellite data, airphotos and airborne Lidar provided in the past the necessary data for the coastline monitoring. High-resolution digital surface models (DSMs) and orthophoto maps had become a necessity in order to map with accuracy all the variations in costal environments. Recently, unmanned aerial vehicles (UAV) photogrammetry offers an alternative solution to the acquisition of high accuracy spatial data along the coastline. This paper presents the use of UAV to map the coastline in Rio area Western Greece. Multiple photogrammetric aerial campaigns were performed. A small commercial UAV (DJI Phantom 3 Advance) was used to acquire thousands of images with spatial resolutions better than 5 cm. Different photogrammetric software's were used to orientate the images, extract point clouds, build a digital surface model and produce orthoimage mosaics. In order to achieve the best positional accuracy signalised ground control points were measured with a differential GNSS receiver. The results of this coastal monitoring programme proved that UAVs can replace many of the conventional surveys, with considerable gains in the cost of the data acquisition and without any loss in the accuracy.

Monitoring Inflation and Emplacement During the 2014-2015 Kilauea Lava Flow With an Unmanned Aerial Vehicle

NASA Astrophysics Data System (ADS)

Perroy, R. L.; Turner, N.; Hon, K. A.; Rasgado, V.

2015-12-01

Unmanned aerial vehicles (UAVs) provide a powerful new tool for collecting high resolution on-demand spatial data over volcanic eruptions and other active geomorphic processes. These data can be used to improve hazard forecasts and emergency response efforts, and also allow users to economically and safely observe and quantify lava flow inflation and emplacement on spatially and temporally useful scales. We used a small fixed-wing UAV with a modified point-and-shoot camera to repeatedly map the active front of the 2014-2015 Kīlauea lava flow over a one-month period in late 2014, at times with a two-hour repeat interval. An additional subsequent flight was added in July, 2015. We used the imagery from these flights to generate a time-series of 5-cm resolution RGB and near-infrared orthoimagery mosaics and associated digital surface models using structure from motion. Survey-grade positional control was provided by ground control points with differential GPS. Two topographic transects were repeatedly surveyed across the flow surface, contemporaneously with UAV flights, to independently confirm topographic changes observed in the UAV-derived surface models. Vertical errors were generally 10 cm. Inside our 50 hectare study site, the flow advanced at a rate of 0.47 hectares/day during the first three weeks of observations before abruptly stalling out <200 m from Pahoa Village road. Over 150,000 m3of lava were added to the study site during our period of observations, with maximum vertical inflation >4 m. New outbreak areas, both on the existing flow surface and along the flow margins, were readily mapped across the study area. We detected sinuous growing inflation ridges within the flow surface that correlated with subsequent outbreaks of new lava, suggesting that repeat UAV flights can provide a means of better predicting pahoehoe lava flow behavior over flat or uneven topography. Our results show that UAVs can generate accurate and digital surface models quickly and inexpensively over rapidly changing active pahoehoe lava flows.

Scaling forest phenology from trees to the landscape using an unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Klosterman, S.; Melaas, E. K.; Martinez, A.; Richardson, A. D.

2013-12-01

Vegetation phenology monitoring has yielded a decades-long archive documenting the impacts of global change on the biosphere. However, the coarse spatial resolution of remote sensing obscures the organismic level processes driving phenology, while point measurements on the ground limit the extent of observation. Unmanned aerial vehicles (UAVs) enable low altitude remote sensing at higher spatial and temporal resolution than available from space borne platforms, and have the potential to elucidate the links between organism scale processes and landscape scale analyses of terrestrial phenology. This project demonstrates the use of a low cost multirotor UAV, equipped with a consumer grade digital camera, for observation of deciduous forest phenology and comparison to ground- and tower-based data as well as remote sensing. The UAV was flown approximately every five days during the spring green-up period in 2013, to obtain aerial photography over an area encompassing a 250m resolution MODIS (Moderate Resolution Imaging Spectroradiometer) pixel at Harvard Forest in central Massachusetts, USA. The imagery was georeferenced and tree crowns were identified using a detailed species map of the study area. Image processing routines were used to extract canopy 'greenness' time series, which were used to calculate phenology transition dates corresponding to early, middle, and late stages of spring green-up for the dominant canopy trees. Aggregated species level phenology estimates from the UAV data, including the mean and variance of phenology transition dates within species in the study area, were compared to model predictions based on visual assessment of a smaller sample size of individual trees, indicating the extent to which limited ground observations represent the larger landscape. At an intermediate scale, the UAV data was compared to data from repeat digital photography, integrating over larger portions of canopy within and near the study area, as a validation step and to see how well tower-based approaches characterize the surrounding landscape. Finally, UAV data was compared to MODIS data to determine how tree crowns within a remote sensing pixel combine to create the aggregate landscape phenology measured by remote sensing, using an area weighted average of the phenology of all dominant crowns.

Development and Integration of a Solar Powered Unmanned Aerial Vehicle and a Wireless Sensor Network to Monitor Greenhouse Gases

PubMed Central

Malaver, Alexander; Motta, Nunzio; Corke, Peter; Gonzalez, Felipe

2015-01-01

Measuring gases for environmental monitoring is a demanding task that requires long periods of observation and large numbers of sensors. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) currently represent the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialized gas sensing systems. This paper presents the development and integration of a WSN and an UAV powered by solar energy in order to enhance their functionality and broader their applications. A gas sensing system implementing nanostructured metal oxide (MOX) and non-dispersive infrared sensors was developed to measure concentrations of CH4 and CO2. Laboratory, bench and field testing results demonstrate the capability of UAV to capture, analyze and geo-locate a gas sample during flight operations. The field testing integrated ground sensor nodes and the UAV to measure CO2 concentration at ground and low aerial altitudes, simultaneously. Data collected during the mission was transmitted in real time to a central node for analysis and 3D mapping of the target gas. The results highlights the accomplishment of the first flight mission of a solar powered UAV equipped with a CO2 sensing system integrated with a WSN. The system provides an effective 3D monitoring and can be used in a wide range of environmental applications such as agriculture, bushfires, mining studies, zoology and botanical studies using a ubiquitous low cost technology. PMID:25679312

Development and integration of a solar powered unmanned aerial vehicle and a wireless sensor network to monitor greenhouse gases.

PubMed

Malaver, Alexander; Motta, Nunzio; Corke, Peter; Gonzalez, Felipe

2015-02-11

Measuring gases for environmental monitoring is a demanding task that requires long periods of observation and large numbers of sensors. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) currently represent the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialized gas sensing systems. This paper presents the development and integration of a WSN and an UAV powered by solar energy in order to enhance their functionality and broader their applications. A gas sensing system implementing nanostructured metal oxide (MOX) and non-dispersive infrared sensors was developed to measure concentrations of CH4 and CO2. Laboratory, bench and field testing results demonstrate the capability of UAV to capture, analyze and geo-locate a gas sample during flight operations. The field testing integrated ground sensor nodes and the UAV to measure CO2 concentration at ground and low aerial altitudes, simultaneously. Data collected during the mission was transmitted in real time to a central node for analysis and 3D mapping of the target gas. The results highlights the accomplishment of the first flight mission of a solar powered UAV equipped with a CO2 sensing system integrated with a WSN. The system provides an effective 3D monitoring and can be used in a wide range of environmental applications such as agriculture, bushfires, mining studies, zoology and botanical studies using a ubiquitous low cost technology.

Automatic Hotspot and Sun Glint Detection in UAV Multispectral Images

PubMed Central

Ortega-Terol, Damian; Ballesteros, Rocio

2017-01-01

Last advances in sensors, photogrammetry and computer vision have led to high-automation levels of 3D reconstruction processes for generating dense models and multispectral orthoimages from Unmanned Aerial Vehicle (UAV) images. However, these cartographic products are sometimes blurred and degraded due to sun reflection effects which reduce the image contrast and colour fidelity in photogrammetry and the quality of radiometric values in remote sensing applications. This paper proposes an automatic approach for detecting sun reflections problems (hotspot and sun glint) in multispectral images acquired with an Unmanned Aerial Vehicle (UAV), based on a photogrammetric strategy included in a flight planning and control software developed by the authors. In particular, two main consequences are derived from the approach developed: (i) different areas of the images can be excluded since they contain sun reflection problems; (ii) the cartographic products obtained (e.g., digital terrain model, orthoimages) and the agronomical parameters computed (e.g., normalized vegetation index-NVDI) are improved since radiometric defects in pixels are not considered. Finally, an accuracy assessment was performed in order to analyse the error in the detection process, getting errors around 10 pixels for a ground sample distance (GSD) of 5 cm which is perfectly valid for agricultural applications. This error confirms that the precision in the detection of sun reflections can be guaranteed using this approach and the current low-cost UAV technology. PMID:29036930

Automatic Hotspot and Sun Glint Detection in UAV Multispectral Images.

PubMed

Ortega-Terol, Damian; Hernandez-Lopez, David; Ballesteros, Rocio; Gonzalez-Aguilera, Diego

2017-10-15

Last advances in sensors, photogrammetry and computer vision have led to high-automation levels of 3D reconstruction processes for generating dense models and multispectral orthoimages from Unmanned Aerial Vehicle (UAV) images. However, these cartographic products are sometimes blurred and degraded due to sun reflection effects which reduce the image contrast and colour fidelity in photogrammetry and the quality of radiometric values in remote sensing applications. This paper proposes an automatic approach for detecting sun reflections problems (hotspot and sun glint) in multispectral images acquired with an Unmanned Aerial Vehicle (UAV), based on a photogrammetric strategy included in a flight planning and control software developed by the authors. In particular, two main consequences are derived from the approach developed: (i) different areas of the images can be excluded since they contain sun reflection problems; (ii) the cartographic products obtained (e.g., digital terrain model, orthoimages) and the agronomical parameters computed (e.g., normalized vegetation index-NVDI) are improved since radiometric defects in pixels are not considered. Finally, an accuracy assessment was performed in order to analyse the error in the detection process, getting errors around 10 pixels for a ground sample distance (GSD) of 5 cm which is perfectly valid for agricultural applications. This error confirms that the precision in the detection of sun reflections can be guaranteed using this approach and the current low-cost UAV technology.

Experiment on Uav Photogrammetry and Terrestrial Laser Scanning for Ict-Integrated Construction

NASA Astrophysics Data System (ADS)

Takahashi, N.; Wakutsu, R.; Kato, T.; Wakaizumi, T.; Ooishi, T.; Matsuoka, R.

2017-08-01

In the 2016 fiscal year the Ministry of Land, Infrastructure, Transport and Tourism of Japan started a program integrating construction and ICT in earthwork and concrete placing. The new program named "i-Construction" focusing on productivity improvement adopts such new technologies as UAV photogrammetry and TLS. We report a field experiment to investigate whether the procedures of UAV photogrammetry and TLS following the standards for "i-Construction" are feasible or not. In the experiment we measured an embankment of about 80 metres by 160 metres immediately after earthwork was done on the embankment. We used two sets of UAV and camera in the experiment. One is a larger UAV enRoute Zion QC730 and its onboard camera Sony α6000. The other is a smaller UAV DJI Phantom 4 and its dedicated onboard camera. Moreover, we used a terrestrial laser scanner FARO Focus3D X330 based on the phase shift principle. The experiment results indicate that the procedures of UAV photogrammetry using a QC730 with an α6000 and TLS using a Focus3D X330 following the standards for "i-Construction" would be feasible. Furthermore, the experiment results show that UAV photogrammetry using a lower price UAV Phantom 4 was unable to satisfy the accuracy requirement for "i-Construction." The cause of the low accuracy by Phantom 4 is under investigation. We also found that the difference of image resolution on the ground would not have a great influence on the measurement accuracy in UAV photogrammetry.

Smart Cruise Control: UAV sensor operator intent estimation and its application

NASA Astrophysics Data System (ADS)

Cheng, Hui; Butler, Darren; Kumar, Rakesh

2006-05-01

Due to their long endurance, superior mobility and the low risk posed to the pilot and sensor operator, UAVs have become the preferred platform for persistent ISR missions. However, currently most UAV based ISR missions are conducted through manual operation. Event the simplest tasks, such as vehicle tracking, route reconnaissance and site monitoring, need the sensor operator's undivided attention and constant adjustment of the sensor control. The lack of autonomous behaviour greatly limits of the effectiveness and the capability of UAV-based ISR, especially the use of a large number of UAVs simultaneously. Although fully autonomous UAV based ISR system is desirable, it is still a distant dream due to the complexity and diversity of combat and ISR missions. In this paper, we propose a Smart Cruise Control system that can learn UAV sensor operator's intent and use it to complete tasks automatically, such as route reconnaissance and site monitoring. Using an operator attention model, the proposed system can estimate the operator's intent from how they control the sensor (e.g. camera) and the content of the imagery that is acquired. Therefore, for example, from initially manually controlling the UAV sensor to follow a road, the system can learn not only the preferred operation, "tracking", but also the road appearance, "what to track" in real-time. Then, the learnt models of both road and the desired operation can be used to complete the task automatically. We have demonstrated the Smart Cruise Control system using real UAV videos where roads need to be tracked and buildings need to be monitored.

Application of Artificial Intelligence Techniques in Unmanned Aerial Vehicle Flight

NASA Technical Reports Server (NTRS)

Bauer, Frank H. (Technical Monitor); Dufrene, Warren R., Jr.

2003-01-01

This paper describes the development of an application of Artificial Intelligence for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in Artificial Intelligence (AI) at Nova southeastern University and as an adjunct to a project at NASA Goddard Space Flight Center's Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an AI method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed. A low cost approach was taken using freeware, gnu, software, and demo programs. The focus of this research has been to outline some of the AI techniques used for UAV flight control and discuss some of the tools used to apply AI techniques. The intent is to succeed with the implementation of applying AI techniques to actually control different aspects of the flight of an UAV.

Sensor data fusion for automated threat recognition in manned-unmanned infantry platoons

NASA Astrophysics Data System (ADS)

Wildt, J.; Varela, M.; Ulmke, M.; Brüggermann, B.

2017-05-01

To support a dismounted infantry platoon during deployment we team it with several unmanned aerial and ground vehicles (UAV and UGV, respectively). The unmanned systems integrate seamlessly into the infantry platoon, providing automated reconnaissance during movement while keeping formation as well as conducting close range reconnaissance during halt. The sensor data each unmanned system provides is continuously analyzed in real time by specialized algorithms, detecting humans in live videos of UAV mounted infrared cameras as well as gunshot detection and bearing by acoustic sensors. All recognized threats are fused into a consistent situational picture in real time, available to platoon and squad leaders as well as higher level command and control (C2) systems. This gives friendly forces local information superiority and increased situational awareness without the need to constantly monitor the unmanned systems and sensor data.

Using UAV data for soil surface change detection at a loess field plot

NASA Astrophysics Data System (ADS)

Eltner, Anette; Baumgart, Philipp

2014-05-01

Application of unmanned aerial vehicles (UAV) denotes an increasing interest in geosciences due to major developments within the last years. Today, UAV are economical, reliable and flexible in usage. They provide a non-invasive method to measure the soil surface and its changes - e.g. due to erosion - with high resolution. Advances in digital photogrammetry and computer vision allow for fast and dense digital surface reconstruction from overlapping images. The study site is located in the Saxonian loess (Germany). The area is fragile due to erodible soils and intense agricultural utilisation. Hence, detectable soil surface changes are expected. The size of the field plot is 20 x 30 meters and the period of investigation lasts from October 2012 till July 2013 at which four surveys were performed. The UAV deployed in this study is equipped with a compact camera which is attached to an active stabilising camera mount. In addition, the micro drone integrates GPS and IMU that enables autonomous surveys with programmed flight patterns. About 100 photos are needed to cover the study site at a minimal flying height of eight metres and 65%/80% image overlap. For multi-temporal comparison a stable local reference system is established. Total station control of the signalised ground control points confirms two mm accuracy for the study period. To estimate the accuracy of the digital surface models (DSM) derived from the UAV images a comparison to DSM from terrestrial laser scanning (TLS) is conducted. The standard deviation of differences amounts five millimetres. To analyse surface changes methods from image processing are applied to the DSM. Erosion rills could be extracted for quantitative and qualitative consideration. Furthermore, volumetric changes are measured. First results indicate levelling processes during the winter season and reveal rill and inter-rill erosion during spring and summer season.

Landslide Mapping Using Imagery Acquired by a Fixed-Wing Uav

NASA Astrophysics Data System (ADS)

Rau, J. Y.; Jhan, J. P.; Lo, C. F.; Lin, Y. S.

2011-09-01

In Taiwan, the average annual rainfall is about 2,500 mm, about three times the world average. Hill slopes where are mostly under meta-stable conditions due to fragmented surface materials can easily be disturbed by heavy typhoon rainfall and/or earthquakes, resulting in landslides and debris flows. Thus, an efficient data acquisition and disaster surveying method is critical for decision making. Comparing with satellite and airplane, the unmanned aerial vehicle (UAV) is a portable and dynamic platform for data acquisition. In particularly when a small target area is required. In this study, a fixed-wing UAV that equipped with a consumer grade digital camera, i.e. Canon EOS 450D, a flight control computer, a Garmin GPS receiver and an attitude heading reference system (AHRS) are proposed. The adopted UAV has about two hours flight duration time with a flight control range of 20 km and has a payload of 3 kg, which is suitable for a medium scale mapping and surveying mission. In the paper, a test area with 21.3 km2 in size containing hundreds of landslides induced by Typhoon Morakot is used for landslides mapping. The flight height is around 1,400 meters and the ground sampling distance of the acquired imagery is about 17 cm. The aerial triangulation, ortho-image generation and mosaicking are applied to the acquired images in advance. An automatic landslides detection algorithm is proposed based on the object-based image analysis (OBIA) technique. The color ortho-image and a digital elevation model (DEM) are used. The ortho-images before and after typhoon are utilized to estimate new landslide regions. Experimental results show that the developed algorithm can achieve a producer's accuracy up to 91%, user's accuracy 84%, and a Kappa index of 0.87. It demonstrates the feasibility of the landslide detection algorithm and the applicability of a fixed-wing UAV for landslide mapping.

Nonlinear Landing Control for Quadrotor UAVs

NASA Astrophysics Data System (ADS)

Voos, Holger

Quadrotor UAVs are one of the most preferred type of small unmanned aerial vehicles because of the very simple mechanical construction and propulsion principle. However, the nonlinear dynamic behavior requires a more advanced stabilizing control and guidance of these vehicles. In addition, the small payload reduces the amount of batteries that can be carried and thus also limits the operating range of the UAV. One possible solution for a range extension is the application of a mobile base station for recharging purpose even during operation. However, landing on a moving base station requires autonomous tracking and landing control of the UAV. In this paper, a nonlinear autopilot for quadrotor UAVs is extended with a tracking and landing controller to fulfill the required task.

Generation and Assessment of High Resolution Digital Surface Model by Using Unmanned Air Vehicle Based Multicopter

NASA Astrophysics Data System (ADS)

Gülci, S.; Dindaroğlu, T.; Gündoğan, R.

2017-11-01

Unmanned air vehicle systems (UAVSs), which are presently defined as effective measuring instruments, can be used for measurements and evaluation studies in fields. Furthermore, UAVs are effective tools that can produce high-precision and resolution data for use in geographic information system-based work. This study examined a multicopter (hexacopter) as an air platform to seek opportunity in generating DSM with high resolution. Flights were performed in Kahramanmaras Sutcu Imam University Campus area in Turkey. Pre-assessment of field works, mission, tests and installation were prepared by using a Laptop with an adaptive ground control station. Hand remote controller unit was also linked and activated during flight to interfere with emergency situations. Canon model IXSUS 160 was preferred as sensor. As a result of this study, as mentioned previous studies, .The orthophotos can be produced by RGB (Red-green-blue) images obtained with UAV, herewith information on terrain topography, land cover and soil erosion can be evaluated.

Autonomous Inspection of Electrical Transmission Structures with Airborne UV Sensors - NASA Report on Dominion Virginia Power Flights of November 2016

NASA Technical Reports Server (NTRS)

Moore, Andrew J.; Schubert, Matthew; Nicholas Rymer

2017-01-01

The report details test and measurement flights to demonstrate autonomous UAV inspection of high voltage electrical transmission structures. A UAV built with commercial, off-the-shelf hardware and software, supplemented with custom sensor logging software, measured ultraviolet emissions from a test generator placed on a low-altitude substation and a medium-altitude switching tower. Since corona discharge precedes catastrophic electrical faults on high-voltage structures, detection and geolocation of ultraviolet emissions is needed to develop a UAV-based self-diagnosing power grid. Signal readings from an onboard ultraviolet sensor were validated during flight with a commercial corona camera. Geolocation was accomplished with onboard GPS; the UAV position was logged to a local ground station and transmitted in real time to a NASA server for tracking in the national airspace.

Capabilities Assessment and Employment Recommendations for Full Motion Video Optical Navigation Exploitation (FMV-ONE)

DTIC Science & Technology

2015-06-01

GEOINT geospatial intelligence GFC ground force commander GPS global positioning system GUI graphical user interface HA/DR humanitarian...transport stream UAS unmanned aerial system . See UAV. UAV unmanned aerial vehicle. See UAS. VM virtual machine VMU Marine Unmanned Aerial Vehicle... Unmanned Air Systems (UASs). Current programs promise to dramatically increase the number of FMV feeds in the near future. However, there are too

Direct Georeferencing of Uav Data Based on Simple Building Structures

NASA Astrophysics Data System (ADS)

Tampubolon, W.; Reinhardt, W.

2016-06-01

Unmanned Aerial Vehicle (UAV) data acquisition is more flexible compared with the more complex traditional airborne data acquisition. This advantage puts UAV platforms in a position as an alternative acquisition method in many applications including Large Scale Topographical Mapping (LSTM). LSTM, i.e. larger or equal than 1:10.000 map scale, is one of a number of prominent priority tasks to be solved in an accelerated way especially in third world developing countries such as Indonesia. As one component of fundamental geospatial data sets, large scale topographical maps are mandatory in order to enable detailed spatial planning. However, the accuracy of the products derived from the UAV data are normally not sufficient for LSTM as it needs robust georeferencing, which requires additional costly efforts such as the incorporation of sophisticated GPS Inertial Navigation System (INS) or Inertial Measurement Unit (IMU) on the platform and/or Ground Control Point (GCP) data on the ground. To reduce the costs and the weight on the UAV alternative solutions have to be found. This paper outlines a direct georeferencing method of UAV data by providing image orientation parameters derived from simple building structures and presents results of an investigation on the achievable results in a LSTM application. In this case, the image orientation determination has been performed through sequential images without any input from INS/IMU equipment. The simple building structures play a significant role in such a way that geometrical characteristics have been considered. Some instances are the orthogonality of the building's wall/rooftop and the local knowledge of the building orientation in the field. In addition, we want to include the Structure from Motion (SfM) approach in order to reduce the number of required GCPs especially for the absolute orientation purpose. The SfM technique applied to the UAV data and simple building structures additionally presents an effective tool for the LSTM application at low cost. Our results show that image orientation calculations from building structure essentially improve the accuracy of direct georeferencing procedure adjusted also by the GCPs. To gain three dimensional (3D) point clouds in local coordinate system, an extraction procedure has been performed by using Agisoft Photo Scan. Subsequently, a Digital Surface Model (DSM) generated from the acquired data is the main output for LSTM that has to be assessed using standard field and conventional mapping workflows. For an appraisal, our DSM is compared directly with a similar DSM obtained by conventional airborne data acquisition using Leica RCD-30 metric camera as well as Trimble Phase One (P65+) camera. The comparison reveals that our approach can achieve meter level accuracy both in planimetric and vertical dimensions.

Evaluating rapid ground sampling and scaling estimated plant cover using UAV imagery up to Landsat for mapping arctic vegetation

NASA Astrophysics Data System (ADS)

Nelson, P.; Paradis, D. P.

2017-12-01

The small stature and spectral diversity of arctic plant taxa presents challenges in mapping arctic vegetation. Mapping vegetation at the appropriate scale is needed to visualize effects of disturbance, directional vegetation change or mapping of specific plant groups for other applications (eg. habitat mapping). Fine spatial grain of remotely sensed data (ca. 10 cm pixels) is often necessary to resolve patches of many arctic plant groups, such as bryophytes and lichens. These groups are also spectrally different from mineral, litter and vascular plants. We sought to explore method to generate high-resolution spatial and spectral data to explore better mapping methods for arctic vegetation. We sampled ground vegetation at seven sites north or west of tree-line in Alaska, four north of Fairbanks and three northwest of Bethel, respectively. At each site, we estimated cover of plant functional types in 1m2 quadrats spaced approximately every 10 m along a 100 m long transect. Each quadrat was also scanned using a field spectroradiometer (PSR+ Spectral Evolution, 400-2500 nm range) and photographed from multiple perspectives. We then flew our small UAV with a RGB camera over the transect and at least 50 m on either side collecting on imagery of the plot, which were used to generate a image mosaic and digital surface model of the plot. We compare plant functional group cover ocular estimated in situ to post-hoc estimation, either automated or using a human observer, using the quadrat photos. We also compare interpolated lichen cover from UAV scenes to estimated lichen cover using a statistical models using Landsat data, with focus on lichens. Light and yellow lichens are discernable in the UAV imagery but certain lichens, especially dark colored lichens or those with spectral signatures similar to graminoid litter, present challenges. Future efforts will focus on integrating UAV-upscaled ground cover estimates to hyperspectral sensors (eg. AVIRIS ng) for better combined spectral and spatial resolution.

Unmanned aerial vehicles (UAVs) in pest management: Progress in the development of a UAV-deployed mating disruption system for Wisconsin cranberries

USDA-ARS?s Scientific Manuscript database

Unmanned aerial vehicles (UAVs) hold significant promise for agriculture. Currently, UAVs are being employed for various reconnaissance purposes (“eyes in the sky”), but not as pest control delivery systems. Research in Wisconsin cranberries is taking UAVs in a new direction. The Steffan and Luck La...

Localization Framework for Real-Time UAV Autonomous Landing: An On-Ground Deployed Visual Approach

PubMed Central

Kong, Weiwei; Hu, Tianjiang; Zhang, Daibing; Shen, Lincheng; Zhang, Jianwei

2017-01-01

One of the greatest challenges for fixed-wing unmanned aircraft vehicles (UAVs) is safe landing. Hereafter, an on-ground deployed visual approach is developed in this paper. This approach is definitely suitable for landing within the global navigation satellite system (GNSS)-denied environments. As for applications, the deployed guidance system makes full use of the ground computing resource and feedbacks the aircraft’s real-time localization to its on-board autopilot. Under such circumstances, a separate long baseline stereo architecture is proposed to possess an extendable baseline and wide-angle field of view (FOV) against the traditional fixed baseline schemes. Furthermore, accuracy evaluation of the new type of architecture is conducted by theoretical modeling and computational analysis. Dataset-driven experimental results demonstrate the feasibility and effectiveness of the developed approach. PMID:28629189

Localization Framework for Real-Time UAV Autonomous Landing: An On-Ground Deployed Visual Approach.

PubMed

Kong, Weiwei; Hu, Tianjiang; Zhang, Daibing; Shen, Lincheng; Zhang, Jianwei

2017-06-19

[-5]One of the greatest challenges for fixed-wing unmanned aircraft vehicles (UAVs) is safe landing. Hereafter, an on-ground deployed visual approach is developed in this paper. This approach is definitely suitable for landing within the global navigation satellite system (GNSS)-denied environments. As for applications, the deployed guidance system makes full use of the ground computing resource and feedbacks the aircraft's real-time localization to its on-board autopilot. Under such circumstances, a separate long baseline stereo architecture is proposed to possess an extendable baseline and wide-angle field of view (FOV) against the traditional fixed baseline schemes. Furthermore, accuracy evaluation of the new type of architecture is conducted by theoretical modeling and computational analysis. Dataset-driven experimental results demonstrate the feasibility and effectiveness of the developed approach.

A survey of hybrid Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Saeed, Adnan S.; Younes, Ahmad Bani; Cai, Chenxiao; Cai, Guowei

2018-04-01

This article presents a comprehensive overview on the recent advances of miniature hybrid Unmanned Aerial Vehicles (UAVs). For now, two conventional types, i.e., fixed-wing UAV and Vertical Takeoff and Landing (VTOL) UAV, dominate the miniature UAVs. Each type has its own inherent limitations on flexibility, payload, flight range, cruising speed, takeoff and landing requirements and endurance. Enhanced popularity and interest are recently gained by the newer type, named hybrid UAV, that integrates the beneficial features of both conventional ones. In this survey paper, a systematic categorization method for the hybrid UAV's platform designs is introduced, first presenting the technical features and representative examples. Next, the hybrid UAV's flight dynamics model and flight control strategies are explained addressing several representative modeling and control work. In addition, key observations, existing challenges and conclusive remarks based on the conducted review are discussed accordingly.

Control of fixed-wing UAV at levelling phase using artificial intelligence

NASA Astrophysics Data System (ADS)

Sayfeddine, Daher

2018-03-01

The increase in the share of fly-by-wire and software controlled UAV is explained by the need to release the human-operator and the desire to reduce the degree of influence of the human factor errors that account for 26% of aircraft accidents. An important reason for the introduction of new control algorithms is also the high level of UAV failures due loss of communication channels and possible hacking. This accounts for 17% of the total number of accidents. The comparison with manned flights shows that the frequency of accidents of unmanned flights is 27,000 times higher. This means that the UAV has 1611 failures per million flight hours and only 0.06 failures at the same time for the manned flight. In view of that, this paper studies the flight autonomy of fixed-wing UAV at the levelling phase. Landing parameters of the UAV are described. They will be used to setup a control scheme for an autopilot based on fuzzy logic algorithm.

Experimental Study of Multispectral Characteristics of an Unmanned Aerial Vehicle at Different Observation Angles

PubMed Central

Zheng, Haijing; Bai, Tingzhu; Wang, Quanxi; Cao, Fengmei; Shao, Long; Sun, Zhaotian

2018-01-01

This study investigates multispectral characteristics of an unmanned aerial vehicle (UAV) at different observation angles by experiment. The UAV and its engine are tested on the ground in the cruise state. Spectral radiation intensities at different observation angles are obtained in the infrared band of 0.9–15 μm by a spectral radiometer. Meanwhile, infrared images are captured separately by long-wavelength infrared (LWIR), mid-wavelength infrared (MWIR), and short-wavelength infrared (SWIR) cameras. Additionally, orientation maps of the radiation area and radiance are obtained. The results suggest that the spectral radiation intensity of the UAV is determined by its exhaust plume and that the main infrared emission bands occur at 2.7 μm and 4.3 μm. At observation angles in the range of 0°–90°, the radiation area of the UAV in MWIR band is greatest; however, at angles greater than 90°, the radiation area in the SWIR band is greatest. In addition, the radiance of the UAV at an angle of 0° is strongest. These conclusions can guide IR stealth technique development for UAVs. PMID:29389880

Dhaksha, the Unmanned Aircraft System in its New Avatar-Automated Aerial Inspection of INDIA'S Tallest Tower

NASA Astrophysics Data System (ADS)

Kumar, K. S.; Rasheed, A. Mohamed; Krishna Kumar, R.; Giridharan, M.; Ganesh

2013-08-01

DHAKSHA, the unmanned aircraft system (UAS), developed after several years of research by Division of Avionics, Department of Aerospace Engineering, MIT Campus of Anna University has recently proved its capabilities during May 2012 Technology demonstration called UAVforge organised by Defence Research Project Agency, Department of Defence, USA. Team Dhaksha with its most stable design outperformed all the other contestants competing against some of the best engineers from prestigi ous institutions across the globe like Middlesex University from UK, NTU and NUS from Singapore, Tudelft Technical University, Netherlands and other UAV industry participants in the world's toughest UAV challenge. This has opened up an opportunity for Indian UAVs making a presence in the international scenario as well. In furtherance to the above effort at Fort Stewart military base at Georgia,USA, with suitable payloads, the Dhaksha team deployed the UAV in a religious temple festival during November 2012 at Thiruvannamalai District for Tamil Nadu Police to avail the instant aerial imagery services over the crowd of 10 lakhs pilgrims and also about the investigation of the structural strength of the India's tallest structure, the 300 m RCC tower during January 2013. The developed system consists of a custom-built Rotary Wing model with on-board navigation, guidance and control systems (NGC) and ground control station (GCS), for mission planning, remote access, manual overrides and imagery related computations. The mission is to fulfill the competition requirements by using an UAS capable of providing complete solution for the stated problem. In this work the effort to produce multirotor unmanned aerial systems (UAS) for civilian applications at the MIT, Avionics Laboratory is presented

UAV State Estimation Modeling Techniques in AHRS

NASA Astrophysics Data System (ADS)

Razali, Shikin; Zhahir, Amzari

2017-11-01

Autonomous unmanned aerial vehicle (UAV) system is depending on state estimation feedback to control flight operation. Estimation on the correct state improves navigation accuracy and achieves flight mission safely. One of the sensors configuration used in UAV state is Attitude Heading and Reference System (AHRS) with application of Extended Kalman Filter (EKF) or feedback controller. The results of these two different techniques in estimating UAV states in AHRS configuration are displayed through position and attitude graphs.

An arm wearable haptic interface for impact sensing on unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Choi, Yunshil; Hong, Seung-Chan; Lee, Jung-Ryul

2017-04-01

In this paper, an impact monitoring system using fiber Bragg grating (FBG) sensors and vibro-haptic actuators has been introduced. The system is suggested for structural health monitoring (SHM) for unmanned aerial vehicles (UAVs), by making a decision with human-robot interaction. The system is composed with two major subsystems; an on-board system equipped on UAV and an arm-wearable interface for ground pilot. The on-board system acquires impact-induced wavelength changes and performs localization process, which was developed based on arrival time calculation. The arm-wearable interface helps ground pilots to make decision about impact location themselves by stimulating their tactile-sense with motor vibration.

Unmanned aerial vehicles (UAVs) in pest management: Progress in the development of a UAV-deployed mating disruption system for Wisconsin cranberries

USDA-ARS?s Scientific Manuscript database

Unmanned aerial vehicles (UAVs) represent a powerful new tool for agriculture. Currently, UAVs are used almost exclusively as crop reconnaissance devices (“eyes in the sky”), not as pest control delivery systems. Research in Wisconsin cranberries is taking UAVs in a new direction. The Steffan and Lu...

A survey of unmanned ground vehicles with applications to agricultural and environmental sensing

NASA Astrophysics Data System (ADS)

Bonadies, Stephanie; Lefcourt, Alan; Gadsden, S. Andrew

2016-05-01

Unmanned ground vehicles have been utilized in the last few decades in an effort to increase the efficiency of agriculture, in particular, by reducing labor needs. Unmanned vehicles have been used for a variety of purposes including: soil sampling, irrigation management, precision spraying, mechanical weeding, and crop harvesting. In this paper, unmanned ground vehicles, implemented by researchers or commercial operations, are characterized through a comparison to other vehicles used in agriculture, namely airplanes and UAVs. An overview of different trade-offs of configurations, control schemes, and data collection technologies is provided. Emphasis is given to the use of unmanned ground vehicles in food crops, and includes a discussion of environmental impacts and economics. Factors considered regarding the future trends and potential issues of unmanned ground vehicles include development, management and performance. Also included is a strategy to demonstrate to farmers the safety and profitability of implementing the technology.

High-performance two-axis gimbal system for free space laser communications onboard unmanned aircraft systems

NASA Astrophysics Data System (ADS)

Locke, Michael; Czarnomski, Mariusz; Qadir, Ashraf; Setness, Brock; Baer, Nicolai; Meyer, Jennifer; Semke, William H.

2011-03-01

A custom designed and manufactured gimbal with a wide field-of-view and fast response time is developed. This enhanced custom design is a 24 volt system with integrated motor controllers and drivers which offers a full 180o fieldof- view in both azimuth and elevation; this provides a more continuous tracking capability as well as increased velocities of up to 479° per second. The addition of active high-frequency vibration control, to complement the passive vibration isolation system, is also in development. The ultimate goal of this research is to achieve affordable, reliable, and secure air-to-air laser communications between two separate remotely piloted aircraft. As a proof-of-concept, the practical implementation of an air-to-ground laserbased video communications payload system flown by a small Unmanned Aerial Vehicle (UAV) will be demonstrated. A numerical tracking algorithm has been written, tested, and used to aim the airborne laser transmitter at a stationary ground-based receiver with known GPS coordinates; however, further refinement of the tracking capabilities is dependent on an improved gimbal design for precision pointing of the airborne laser transmitter. The current gimbal pointing system is a two-axis, commercial-off-the-shelf component, which is limited in both range and velocity. The current design is capable of 360o of pan and 78o of tilt at a velocity of 60o per second. The control algorithm used for aiming the gimbal is executed on a PC-104 format embedded computer onboard the payload to accurately track a stationary ground-based receiver. This algorithm autonomously calculates a line-of-sight vector in real-time by using the UAV autopilot's Differential Global Positioning System (DGPS) which provides latitude, longitude, and altitude and Inertial Measurement Unit (IMU) which provides the roll, pitch, and yaw data, along with the known Global Positioning System (GPS) location of the ground-based photodiode array receiver.

Long-term monitoring of a large landslide by using an Unmanned Aerial Vehicle (UAV)

NASA Astrophysics Data System (ADS)

Lindner, Gerald; Schraml, Klaus; Mansberger, Reinfried; Hübl, Johannes

2015-04-01

Currently UAVs become more and more important in various scientific areas, including forestry, precision farming, archaeology and hydrology. Using these drones in natural hazards research enables a completely new level of data acquisition being flexible of site, invariant in time, cost-efficient and enabling arbitrary spatial resolution. In this study, a rotary-wing Mini-UAV carrying a DSLR camera was used to acquire time series of overlapping aerial images. These photographs were taken as input to extract Digital Surface Models (DSM) as well as orthophotos in the area of interest. The "Pechgraben" area in Upper Austria has a catchment area of approximately 2 km². Geology is mainly dominated by limestone and sandstone. Caused by heavy rainfalls in the late spring of 2013, an area of about 70 ha began to move towards the village in the valley. In addition to the urgent measures, the slow-moving landslide was monitored approximately every month over a time period of more than 18 months. A detailed documentation of the change process was the result. Moving velocities and height differences were quantified and validated using a dense network of Ground Control Points (GCP). For further analysis, 14 image flights with a total amount of 10.000 photographs were performed to create multi-temporal geodata in in sub-decimeter-resolution for two depicted areas of the landslide. Using a UAV for this application proved to be an excellent choice, as it allows short repetition times, low flying heights and high spatial resolution. Furthermore, the UAV acts almost weather independently as well as highly autonomously. High-quality results can be expected within a few hours after the photo flight. The UAV system performs very well in an alpine environment. Time series of the assessed geodata detect changes in topography and provide a long-term documentation of the measures taken in order to stop the landslide and to prevent infrastructure from damage.

The Use of Drones in Spain: Towards a Platform for Controlling UAVs in Urban Environments.

PubMed

Chamoso, Pablo; González-Briones, Alfonso; Rivas, Alberto; Bueno De Mata, Federico; Corchado, Juan Manuel

2018-05-03

Rapid advances in technology make it necessary to prepare our society in every aspect. Some of the most significant technological developments of the last decade are the UAVs (Unnamed Aerial Vehicles) or drones. UAVs provide a wide range of new possibilities and have become a tool that we now use on a daily basis. However, if their use is not controlled, it could entail several risks, which make it necessary to legislate and monitor UAV flights to ensure, inter alia, the security and privacy of all citizens. As a result of this problem, several laws have been passed which seek to regulate their use; however, no proposals have been made with regards to the control of airspace from a technological point of view. This is exactly what we propose in this article: a platform with different modes designed to control UAVs and monitor their status. The features of the proposed platform provide multiple advantages that make the use of UAVs more secure, such as prohibiting UAVs’ access to restricted areas or avoiding collisions between vehicles. The platform has been successfully tested in Salamanca, Spain.

Beach Volume Change Using Uav Photogrammetry Songjung Beach, Korea

NASA Astrophysics Data System (ADS)

Yoo, C. I.; Oh, T. S.

2016-06-01

Natural beach is controlled by many factors related to wave and tidal forces, wind, sediment, and initial topography. For this reason, if numerous topographic data of beach is accurately collected, coastal erosion/acceleration is able to be assessed and clarified. Generally, however, many studies on coastal erosion have limitation to analyse the whole beach, carried out of partial area as like shoreline (horizontal 2D) and beach profile (vertical 2D) on account of limitation of numerical simulation. This is an important application for prevention of coastal erosion, and UAV photogrammetry is also used to 3D topographic data. This paper analyses the use of unmanned aerial vehicles (UAV) to 3D map and beach volume change. UAV (Quadcopter) equipped with a non-metric camera was used to acquire images in Songjung beach which is located south-east Korea peninsula. The dynamics of beach topography, its geometric properties and estimates of eroded and deposited sand volumes were determined by combining elevation data with quarterly RTK-VRS measurements. To explore the new possibilities for assessment of coastal change we have developed a methodology for 3D analysis of coastal topography evolution based on existing high resolution elevation data combined with low coast, UAV and on-ground RTK-VRS surveys. DSMs were obtained by stereo-matching using Agisoft Photoscan. Using GCPs the vertical accuracy of the DSMs was found to be 10 cm or better. The resulting datasets were integrated in a local coordinates and the method proved to be a very useful fool for the detection of areas where coastal erosion occurs and for the quantification of beach change. The value of such analysis is illustrated by applications to coastal of South Korea sites that face significant management challenges.

Woodland Mapping at Single-Tree Levels Using Object-Oriented Classification of Unmanned Aerial Vehicle (uav) Images

NASA Astrophysics Data System (ADS)

Chenari, A.; Erfanifard, Y.; Dehghani, M.; Pourghasemi, H. R.

2017-09-01

Remotely sensed datasets offer a reliable means to precisely estimate biophysical characteristics of individual species sparsely distributed in open woodlands. Moreover, object-oriented classification has exhibited significant advantages over different classification methods for delineation of tree crowns and recognition of species in various types of ecosystems. However, it still is unclear if this widely-used classification method can have its advantages on unmanned aerial vehicle (UAV) digital images for mapping vegetation cover at single-tree levels. In this study, UAV orthoimagery was classified using object-oriented classification method for mapping a part of wild pistachio nature reserve in Zagros open woodlands, Fars Province, Iran. This research focused on recognizing two main species of the study area (i.e., wild pistachio and wild almond) and estimating their mean crown area. The orthoimage of study area was consisted of 1,076 images with spatial resolution of 3.47 cm which was georeferenced using 12 ground control points (RMSE=8 cm) gathered by real-time kinematic (RTK) method. The results showed that the UAV orthoimagery classified by object-oriented method efficiently estimated mean crown area of wild pistachios (52.09±24.67 m2) and wild almonds (3.97±1.69 m2) with no significant difference with their observed values (α=0.05). In addition, the results showed that wild pistachios (accuracy of 0.90 and precision of 0.92) and wild almonds (accuracy of 0.90 and precision of 0.89) were well recognized by image segmentation. In general, we concluded that UAV orthoimagery can efficiently produce precise biophysical data of vegetation stands at single-tree levels, which therefore is suitable for assessment and monitoring open woodlands.

Optimal trajectory planning for a UAV glider using atmospheric thermals

NASA Astrophysics Data System (ADS)

Kagabo, Wilson B.

An Unmanned Aerial Vehicle Glider (UAV glider) uses atmospheric energy in its different forms to remain aloft for extended flight durations. This UAV glider's aim is to extract atmospheric thermal energy and use it to supplement its battery energy usage and increase the mission period. Given an infrared camera identified atmospheric thermal of known strength and location; current wind speed and direction; current battery level; altitude and location of the UAV glider; and estimating the expected altitude gain from the thermal, is it possible to make an energy-efficient based motivation to fly to an atmospheric thermal so as to achieve UAV glider extended flight time? For this work, an infrared thermal camera aboard the UAV glider takes continuous forward-looking ground images of "hot spots". Through image processing a candidate atmospheric thermal strength and location is estimated. An Intelligent Decision Model incorporates this information with the current UAV glider status and weather conditions to provide an energy-based recommendation to modify the flight path of the UAV glider. Research, development, and simulation of the Intelligent Decision Model is the primary focus of this work. Three models are developed: (1) Battery Usage Model, (2) Intelligent Decision Model, and (3) Altitude Gain Model. The Battery Usage Model comes from the candidate flight trajectory, wind speed & direction and aircraft dynamic model. Intelligent Decision Model uses a fuzzy logic based approach. The Altitude Gain Model requires the strength and size of the thermal and is found a priori.

A UAV-Based Fog Collector Design for Fine-Scale Aerobiological Sampling

NASA Technical Reports Server (NTRS)

Gentry, Diana; Guarro, Marcello; Demachkie, Isabella Siham; Stumfall, Isabel; Dahlgren, Robert P.

2017-01-01

Airborne microbes are found throughout the troposphere and into the stratosphere. Knowing how the activity of airborne microorganisms can alter water, carbon, and other geochemical cycles is vital to a full understanding of local and global ecosystems. Just as on the land or in the ocean, atmospheric regions vary in habitability; the underlying geochemical, climatic, and ecological dynamics must be characterized at different scales to be effectively modeled. Most aerobiological studies have focused on a high level: 'How high are airborne microbes found?' and 'How far can they travel?' Most fog and cloud water studies collect from stationary ground stations (point) or along flight transects (1D). To complement and provide context for this data, we have designed a UAV-based modified fog and cloud water collector to retrieve 4D-resolved samples for biological and chemical analysis.Our design uses a passive impacting collector hanging from a rigid rod suspended between two multi-rotor UAVs. The suspension design reduces the effect of turbulence and potential for contamination from the UAV downwash. The UAVs are currently modeled in a leader-follower configuration, taking advantage of recent advances in modular UAVs, UAV swarming, and flight planning.The collector itself is a hydrophobic mesh. Materials including Tyvek, PTFE, nylon, and polypropylene monofilament fabricated via laser cutting, CNC knife, or 3D printing were characterized for droplet collection efficiency using a benchtop atomizer and particle counter. Because the meshes can be easily and inexpensively fabricated, a set can be pre-sterilized and brought to the field for 'hot swapping' to decrease cross-contamination between flight sessions or use as negative controls.An onboard sensor and logging system records the time and location of each sample; when combined with flight tracking data, the samples can be resolved into a 4D volumetric map of the fog bank. Collected samples can be returned to the lab for a variety of analyses. Based on a review of existing flight studies, we have identified ion chromatography, metagenomic sequencing, cell staining and quantification, and ATP quantification as high-priority assays for implementation. Support for specific toxicology assays, such as methylmercury quantification, is also planned.

A UAV-Based Fog Collector Design for Fine-Scale Aerobiological Sampling

NASA Astrophysics Data System (ADS)

Gentry, D.; Guarro, M.; Demachkie, I. S.; Stumfall, I.; Dahlgren, R. P.

2016-12-01

Airborne microbes are found throughout the troposphere and into the stratosphere. Knowing how the activity of airborne microorganisms can alter water, carbon, and other geochemical cycles is vital to a full understanding of local and global ecosystems. Just as on the land or in the ocean, atmospheric regions vary in habitability; the underlying geochemical, climatic, and ecological dynamics must be characterized at different scales to be effectively modeled. Most aerobiological studies have focused on a high level: 'How high are airborne microbes found?' and 'How far can they travel?' Most fog and cloud water studies collect from stationary ground stations (point) or along flight transects (1D). To complement and provide context for this data, we have designed a UAV-based modified fog and cloud water collector to retrieve 4D-resolved samples for biological and chemical analysis. Our design uses a passive impacting collector hanging from a rigid rod suspended between two multi-rotor UAVs. The suspension design reduces the effect of turbulence and potential for contamination from the UAV downwash. The UAVs are currently modeled in a leader-follower configuration, taking advantage of recent advances in modular UAVs, UAV swarming, and flight planning. The collector itself is a hydrophobic mesh. Materials including Tyvek, PTFE, nylon, and polypropylene monofilament fabricated via laser cutting, CNC knife, or 3D printing were characterized for droplet collection efficiency using a benchtop atomizer and particle counter. Because the meshes can be easily and inexpensively fabricated, a set can be pre-sterilized and brought to the field for 'hot swapping' to decrease cross-contamination between flight sessions or use as negative controls. An onboard sensor and logging system records the time and location of each sample; when combined with flight tracking data, the samples can be resolved into a 4D volumetric map of the fog bank. Collected samples can be returned to the lab for a variety of analyses. Based on a review of existing flight studies, we have identified ion chromatography, metagenomic sequencing, cell staining and quantification, and ATP quantification as high-priority assays for implementation. Support for specific toxicology assays, such as methylmercury quantification, is also planned.

Auditory decision aiding in supervisory control of multiple unmanned aerial vehicles.

PubMed

Donmez, Birsen; Cummings, M L; Graham, Hudson D

2009-10-01

This article is an investigation of the effectiveness of sonifications, which are continuous auditory alerts mapped to the state of a monitored task, in supporting unmanned aerial vehicle (UAV) supervisory control. UAV supervisory control requires monitoring a UAV across multiple tasks (e.g., course maintenance) via a predominantly visual display, which currently is supported with discrete auditory alerts. Sonification has been shown to enhance monitoring performance in domains such as anesthesiology by allowing an operator to immediately determine an entity's (e.g., patient) current and projected states, and is a promising alternative to discrete alerts in UAV control. However, minimal research compares sonification to discrete alerts, and no research assesses the effectiveness of sonification for monitoring multiple entities (e.g., multiple UAVs). The authors conducted an experiment with 39 military personnel, using a simulated setup. Participants controlled single and multiple UAVs and received sonifications or discrete alerts based on UAV course deviations and late target arrivals. Regardless of the number of UAVs supervised, the course deviation sonification resulted in reactions to course deviations that were 1.9 s faster, a 19% enhancement, compared with discrete alerts. However, course deviation sonifications interfered with the effectiveness of discrete late arrival alerts in general and with operator responses to late arrivals when supervising multiple vehicles. Sonifications can outperform discrete alerts when designed to aid operators to predict future states of monitored tasks. However, sonifications may mask other auditory alerts and interfere with other monitoring tasks that require divided attention. This research has implications for supervisory control display design.

DECEIVING THE ENEMY: THESE ARE THE DRONES YOU ARE LOOKING FOR

DTIC Science & Technology

2016-06-01

17 UAV Development and Capabilities UAVs have existed since the beginning of the American Civil War when an unmanned balloon carrying explosives...their survival. Control of these MW UAVs can be tethered to the manned aircraft, allowing control by an operator in the formation. Alternatively

Cooperative Mobile Sensing Systems for In Situ Measurements in Hazardous Environments

NASA Astrophysics Data System (ADS)

Argrow, B.

2005-12-01

Sondes are typically deployed from manned aircraft or taken to altitude by a balloon before they are dropped. There are obvious safety and physical limitations that dictate where and how sondes are deployed. These limitations have severely constrained sonde deployment into highly dynamic and dangerous environments. Additionally, conventional parachute dropsondes provide no means for active control. The "smartsonde" idea is to integrate miniature sonde packages into micro air vehicles (MAVs). These MAVs will be ferried into the hard to reach and hazardous environments to provide in situ measurements in regions that have been heretofore out of reach. Once deployed, the MAV will provide some means of control of the sonde, to enable it to remain aloft and to provide some measure of directional control. Preliminary smartsonde communications experiments have been completed. These experiments focused on characterizing the capabilities of the 802.11.4 wireless protocol. Range measurements with 60-mW, 2.4-GHz radios showed 100% throughput rate over 2.7 km during air to ground tests. The experiments also demonstrated the integration of an in-house distributed computing system that provides the interface between the sensors, UAV flight computers, and the telemetry system. The University of Colorado's Research and Engineering Center for Unmanned Vehicles (RECUV) is developing an engineering system that integrates small mobile sensor attributes into flexible mobile sensor infrastructures to be deployed for in situ sensing in hazardous environments. There are three focus applications: 1) Wildfire, to address sensing, communications, situational awareness, and safety needs to support fire-fighting operations and to increase capabilities for dynamic data acquisition for modeling and prediction; 2) Polar, where heterogeneous mixes of platforms and sensors will provide in-situ data acquisition from beneath the ocean surface into the troposphere; 3) Storm, to address the challenges of volumetric in-situ data acquisition in the extremely dynamic environments of severe storms. The common thread among these applications is the need for a cooperative mobile sensing system, where sensor packages are integrated into custom platforms that enable targeting of areas of interest through the cooperative control, with varying levels of autonomy, of small unmanned vehicles. RECUV has demonstrated mobile ad hoc networks using WiFi (802.11b) radios simultaneously deployed in fixed and mobile ground nodes and unmanned aerial vehicles (UAVs). Recently, an autonomous UAV was deployed with a miniature sensor package that returned real-time temperature, pressure, and humidity data, through the ad hoc communications network. The UAV demonstrated the ability to autonomously make flight-path decisions based on the sensor data that was monitored by the flight computer. Current work is now focused on integrating the sensor package into a smartsonde to be deployed from a UAV mothership. Benign scenarios for upcoming tests to validate the collaborative mobile sensing system paradigm include scenarios with features similar to those that will be encountered in the hazardous and dynamic environments a of the wildfire, polar, and storm applications. These include a fly-through of a dust devil on the planes of eastern Colorado and deployment of a dual-mode smartsonde that transmits at high data rates while airborne then, upon landing, it switches to quiet, power-saving mode , where in situ data is logged and only transmitted when the sonde package is queried during overflights of a UAV mothership.

Toward a generic UGV autopilot

NASA Astrophysics Data System (ADS)

Moore, Kevin L.; Whitehorn, Mark; Weinstein, Alejandro J.; Xia, Junjun

2009-05-01

Much of the success of small unmanned air vehicles (UAVs) has arguably been due to the widespread availability of low-cost, portable autopilots. While the development of unmanned ground vehicles (UGVs) has led to significant achievements, as typified by recent grand challenge events, to date the UGV equivalent of the UAV autopilot is not available. In this paper we describe our recent research aimed at the development of a generic UGV autopilot. Assuming we are given a drive-by-wire vehicle that accepts as inputs steering, brake, and throttle commands, we present a system that adds sonar ranging sensors, GPS/IMU/odometry, stereo camera, and scanning laser sensors, together with a variety of interfacing and communication hardware. The system also includes a finite state machine-based software architecture as well as a graphical user interface for the operator control unit (OCU). Algorithms are presented that enable an end-to-end scenario whereby an operator can view stereo images as seen by the vehicle and can input GPS waypoints either from a map or in the vehicle's scene-view image, at which point the system uses the environmental sensors as inputs to a Kalman filter for pose estimation and then computes control actions to move through the waypoint list, while avoiding obstacles. The long-term goal of the research is a system that is generically applicable to any drive-by-wire unmanned ground vehicle.

Rapid melting dynamics of the Morteratsch glacier (Swiss Alps) from UAV photogrammetry and field spectroscopy data

NASA Astrophysics Data System (ADS)

Di Mauro, Biagio; Garzonio, Roberto; Rossini, Micol; Baccolo, Giovanni; Julitta, Tommaso; Cavallini, Giuseppe; Mattavelli, Matteo; Colombo, Roberto

2017-04-01

The impact of atmospheric impurities on the optical properties of snow and ice has been largely acknowledged in the scientific literature. Beyond this, the evaluation of the effect of specific organic and inorganic particles on melting dynamics remains a major challenge. In this contribution, we examine the annual melting dynamics of a large valley glacier of the Swiss Alps using UAV photogrammetry. We then compare the melting patterns to the presence of surface impurities on the glacier surface. Two surveys (in July and September 2016) with a lightweight Unmanned Aerial Vehicle (UAV) were organized on the ablation zone of the Morteratsch glacier (Swiss Alps). The UAV (DJI, Phantom 4) was equipped with a high resolution digital camera, and flew at a constant altitude of 150 from the glacier surface. 30 ground control points were placed on the glacier, and their coordinates were determined with a differential GPS (dGPS) for georeferencing UAV images. Contemporary to the UAV surveys, field spectroscopy data were collected on the glacier surface with an Analytical Spectral Device (ASD Field spec.) spectrometer covering the visible and near infrared spectral ranges, and ice samples were collected to determine the abundance of microorganism and algae. From the UAV RGB data, two point clouds were created using Structure from Motion (SfM) algorithms. The point clouds (each consisting of about 15M points) were then converted in Digital Surface Models (DSM) and orthomosaics by interpolation. The difference between the two DSM was calculated and converted in Snow Water Equivalent (SWE), in order to assess the ice lost by the glacier during the ablation season. The point clouds were compared and the displacement vectors were estimated using different algorithms. The elevation changes estimated from UAV data were compared with the abundance of microorganisms and algae. The reflectance spectra of ice with microorganisms and algae show a chlorophyll absorption feature at 680 nm. The depth of this absorption was extracted from reflectance spectra using a continuum-removal procedure and correlated to the abundance of microorganisms and algae in the snow sample. This result opens interesting perspectives for mapping the spatial distribution of organic material on the glacier surface using remote sensing data, enabling a better understanding of the effect of specific organic particles on melting dynamics.

Application of Artificial Intelligence Techniques in Uninhabited Aerial Vehicle Flight

NASA Technical Reports Server (NTRS)

Dufrene, Warren R., Jr.

2004-01-01

This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA Southeastearn University and a beginning project at NASA Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an Artificial Intelligence method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed.

Application of Artificial Intelligence Techniques in Uninhabitated Aerial Vehicle Flight

NASA Technical Reports Server (NTRS)

Dufrene, Warren R., Jr.

2003-01-01

This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA southeastern University and a beginning project at NASA Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an Artificial Intelligence method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed.

Evaluating horizontal positional accuracy of low-cost UAV orthomosaics over forest terrain using ground control points extracted from different sources

NASA Astrophysics Data System (ADS)

Patias, Petros; Giagkas, Fotis; Georgiadis, Charalampos; Mallinis, Giorgos; Kaimaris, Dimitris; Tsioukas, Vassileios

2017-09-01

Within the field of forestry, forest road mapping and inventory plays an important role in management activities related to wood harvesting industry, sentiment and water run-off modelling, biodiversity distribution and ecological connectivity, recreation activities, future planning of forest road networks and wildfire protection and fire-fighting. Especially in countries of the Mediterranean Rim, knowledge at regional and national scales regarding the distribution and the characteristics of rural and forest road network is essential in order to ensure an effective emergency management and rapid response of the fire-fighting mechanism. Yet, the absence of accurate and updated geodatabases and the drawbacks related to the use of traditional cartographic methods arising from the forest environment settings, and the cost and efforts needed, as thousands of meters need to be surveyed per site, trigger the need for new data sources and innovative mapping approaches. Monitoring the condition of unpaved forest roads with unmanned aerial vehicle technology is an attractive option for substituting objective, laboursome surveys. Although photogrammetric processing of UAV imagery can achieve accuracy of 1-2 centimeters and dense point clouds, the process is commonly based on the establishment of control points. In the case of forest road networks, which are linear features, there is a need for a great number of control points. Our aim is to evaluate low-cost UAV orthoimages generated over forest areas with GCP's captured from existing national scale aerial orthoimagery, satellite imagery available through a web mapping service (WMS), field surveys using Mobile Mapping System and GNSS receiver. We also explored the direct georeferencing potential through the GNSS onboard the low cost UAV. The results suggest that the GNSS approach proved to most accurate, while the positional accuracy derived using the WMS and the aerial orthoimagery datasets deemed satisfactory for the specific task at hand. The direct georeferencing procedure seems to be insufficient unless an onboard GNSS with improved specifications or Real-Time Kinematic (RTK) capabilities is used.

Detection of Nuclear Sources by UAV Teleoperation Using a Visuo-Haptic Augmented Reality Interface

PubMed Central

Micconi, Giorgio; Caselli, Stefano; Benassi, Giacomo; Zambelli, Nicola; Bettelli, Manuele

2017-01-01

A visuo-haptic augmented reality (VHAR) interface is presented enabling an operator to teleoperate an unmanned aerial vehicle (UAV) equipped with a custom CdZnTe-based spectroscopic gamma-ray detector in outdoor environments. The task is to localize nuclear radiation sources, whose location is unknown to the user, without the close exposure of the operator. The developed detector also enables identification of the localized nuclear sources. The aim of the VHAR interface is to increase the situation awareness of the operator. The user teleoperates the UAV using a 3DOF haptic device that provides an attractive force feedback around the location of the most intense detected radiation source. Moreover, a fixed camera on the ground observes the environment where the UAV is flying. A 3D augmented reality scene is displayed on a computer screen accessible to the operator. Multiple types of graphical overlays are shown, including sensor data acquired by the nuclear radiation detector, a virtual cursor that tracks the UAV and geographical information, such as buildings. Experiments performed in a real environment are reported using an intense nuclear source. PMID:28961198

The study of aerosol and ozone measurements in lower boundary layer with UAV helicopter platform

NASA Astrophysics Data System (ADS)

Lin, Po-hsiung; Chen, Wen-nai

2013-04-01

This study describes the aerosol and ozone measurement in the lower atmospheric boundary layer of highly polluted region at Kao-hsiung, Taiwan with a small unmanned aerial vehicle (UAV) helicopter platform. This UAV helicopter, modified from Gaui-X7 electronic-power model helicopter with autopilot AHRS (Altitude-Head-Reference System) kit, has fast climb speed up to 700 m height and keeps stable status for atmospheric measurements in five-minute fly leg. Several quick-replaced battery packages are ready on ground for field intensive observation. The payload rack under this UAV helicopter carries a micro-Aethalometer (black carbon concentration), ozone meter, temperature-humidity sensor, barometer and a time-lapse digital camera. The field measurement site closes to Linyuan Petrochemical Industrial Park, where is one of the heavy polluted regions in Taiwan. Balloon-borne Vaisala RS-92 radiosonde and CL31 Lidar Ceilometer are used to provide the background of the atmosphere at the same time. More data analysis measured by UAV helicopter and its potential application will be discussed.

CO2Explorer: Conducting Greenhouse-Gas Measurements of Landfills using a Small Fixed-wing UAV

NASA Astrophysics Data System (ADS)

Hollingsworth, Peter; Allen, Grant; Kabbabe, Khristopher; Pitt, Joseph

2017-04-01

Quantifying inventories of Greenhouse gas emissions, primarily Methane and Carbon Dioxide, from distributed sources such as a landfill has historically been undertaken using one of several ground based measurement techniques. These methods are either time and/or resource intensive. As a result regulatory agencies have started looking at the potential of using small-unmanned aircraft to supplement or supplant the current methods. The challenge of using a UAV to perform these tasks is the trade-off between accuracy, operational flexibility and operational productivity. This is driven by the state-of-the-art in measurement instruments, the operating environment at landfills and the regulatory/safety environment surrounding UAV operations. This work describes the development of the operational concept, and associated UAV measurement platform for the CO2Explorer. It looks at the scientific, engineering and possible policy trades and compares the use of small rotary and fixed-wing UAVs from both an operational and measurement perspective. This work also makes recommendations on system development and operation for users lacking in both systems engineering and operational experience.

Detection of Nuclear Sources by UAV Teleoperation Using a Visuo-Haptic Augmented Reality Interface.

PubMed

Aleotti, Jacopo; Micconi, Giorgio; Caselli, Stefano; Benassi, Giacomo; Zambelli, Nicola; Bettelli, Manuele; Zappettini, Andrea

2017-09-29

A visuo-haptic augmented reality (VHAR) interface is presented enabling an operator to teleoperate an unmanned aerial vehicle (UAV) equipped with a custom CdZnTe-based spectroscopic gamma-ray detector in outdoor environments. The task is to localize nuclear radiation sources, whose location is unknown to the user, without the close exposure of the operator. The developed detector also enables identification of the localized nuclear sources. The aim of the VHAR interface is to increase the situation awareness of the operator. The user teleoperates the UAV using a 3DOF haptic device that provides an attractive force feedback around the location of the most intense detected radiation source. Moreover, a fixed camera on the ground observes the environment where the UAV is flying. A 3D augmented reality scene is displayed on a computer screen accessible to the operator. Multiple types of graphical overlays are shown, including sensor data acquired by the nuclear radiation detector, a virtual cursor that tracks the UAV and geographical information, such as buildings. Experiments performed in a real environment are reported using an intense nuclear source.

The Small Whiskbroom Imager for atmospheric compositioN monitorinG (SWING) and its operations from an unmanned aerial vehicle (UAV) during the AROMAT campaign

NASA Astrophysics Data System (ADS)

Merlaud, Alexis; Tack, Frederik; Constantin, Daniel; Georgescu, Lucian; Maes, Jeroen; Fayt, Caroline; Mingireanu, Florin; Schuettemeyer, Dirk; Meier, Andreas Carlos; Schönardt, Anja; Ruhtz, Thomas; Bellegante, Livio; Nicolae, Doina; Den Hoed, Mirjam; Allaart, Marc; Van Roozendael, Michel

2018-01-01

The Small Whiskbroom Imager for atmospheric compositioN monitorinG (SWING) is a compact remote sensing instrument dedicated to mapping trace gases from an unmanned aerial vehicle (UAV). SWING is based on a compact visible spectrometer and a scanning mirror to collect scattered sunlight. Its weight, size, and power consumption are respectively 920 g, 27 cm × 12 cm × 8 cm, and 6 W. SWING was developed in parallel with a 2.5 m flying-wing UAV. This unmanned aircraft is electrically powered, has a typical airspeed of 100 km h-1, and can operate at a maximum altitude of 3 km. We present SWING-UAV experiments performed in Romania on 11 September 2014 during the Airborne ROmanian Measurements of Aerosols and Trace gases (AROMAT) campaign, which was dedicated to test newly developed instruments in the context of air quality satellite validation. The UAV was operated up to 700 m above ground, in the vicinity of the large power plant of Turceni (44.67° N, 23.41° E; 116 m a. s. l. ). These SWING-UAV flights were coincident with another airborne experiment using the Airborne imaging differential optical absorption spectroscopy (DOAS) instrument for Measurements of Atmospheric Pollution (AirMAP), and with ground-based DOAS, lidar, and balloon-borne in situ observations. The spectra recorded during the SWING-UAV flights are analysed with the DOAS technique. This analysis reveals NO2 differential slant column densities (DSCDs) up to 13±0.6×1016 molec cm-2. These NO2 DSCDs are converted to vertical column densities (VCDs) by estimating air mass factors. The resulting NO2 VCDs are up to 4.7±0.4×1016 molec cm-2. The water vapour DSCD measurements, up to 8±0.15×1022 molec cm-2, are used to estimate a volume mixing ratio of water vapour in the boundary layer of 0.013±0.002 mol mol-1. These geophysical quantities are validated with the coincident measurements.

UAV-based Radar Sounding of Antarctic Ice

NASA Astrophysics Data System (ADS)

Leuschen, Carl; Yan, Jie-Bang; Mahmood, Ali; Rodriguez-Morales, Fernando; Hale, Rick; Camps-Raga, Bruno; Metz, Lynsey; Wang, Zongbo; Paden, John; Bowman, Alec; Keshmiri, Shahriar; Gogineni, Sivaprasad

2014-05-01

We developed a compact radar for use on a small UAV to conduct measurements over the ice sheets in Greenland and Antarctica. It operates at center frequencies of 14 and 35 MHz with bandwidths of 1 MHz and 4 MHz, respectively. The radar weighs about 2 kgs and is housed in a box with dimensions of 20.3 cm x 15.2 cm x 13.2 cm. It transmits a signal power of 100 W at a pulse repletion frequency of 10 kHz and requires average power of about 20 W. The antennas for operating the radar are integrated into the wings and airframe of a small UAV with a wingspan of 5.3 m. We selected the frequencies of 14 and 35 MHz based on previous successful soundings of temperate ice in Alaska with a 12.5 MHz impulse radar [Arcone, 2002] and temperate glaciers in Patagonia with a 30 MHz monocycle radar [Blindow et al., 2012]. We developed the radar-equipped UAV to perform surveys over a 2-D grid, which allows us to synthesize a large two-dimensional aperture and obtain fine resolution in both the along- and cross-track directions. Low-frequency, high-sensitivity radars with 2-D aperture synthesis capability are needed to overcome the surface and volume scatter that masks weak echoes from the ice-bed interface of fast-flowing glaciers. We collected data with the radar-equipped UAV on sub-glacial ice near Lake Whillans at both 14 and 35 MHz. We acquired data to evaluate the concept of 2-D aperture synthesis and successfully demonstrated the first successful sounding of ice with a radar on an UAV. We are planning to build multiple radar-equipped UAVs for collecting fine-resolution data near the grounding lines of fast-flowing glaciers. In this presentation we will provide a brief overview of the radar and UAV, as well as present results obtained at both 14 and 35 MHz. Arcone, S. 2002. Airborne-radar stratigraphy and electrical structure of temperate firn: Bagley Ice Field, Alaska, U.S.A. Journal of Glaciology, 48, 317-334. Blindow, N., C. Salat, and G. Casassa. 2012. Airborne GPR sounding of deep temperate glaciers—examples from the Northern Patagonian Icefield, 14th International Conference on Ground Penetrating Radar (GPR) June 4-8, 2012, Shanghai, China, ISBN 978-1-4673-2663-6.

[Comparison of precision in retrieving soybean leaf area index based on multi-source remote sensing data].

PubMed

Gao, Lin; Li, Chang-chun; Wang, Bao-shan; Yang Gui-jun; Wang, Lei; Fu, Kui

2016-01-01

With the innovation of remote sensing technology, remote sensing data sources are more and more abundant. The main aim of this study was to analyze retrieval accuracy of soybean leaf area index (LAI) based on multi-source remote sensing data including ground hyperspectral, unmanned aerial vehicle (UAV) multispectral and the Gaofen-1 (GF-1) WFV data. Ratio vegetation index (RVI), normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), difference vegetation index (DVI), and triangle vegetation index (TVI) were used to establish LAI retrieval models, respectively. The models with the highest calibration accuracy were used in the validation. The capability of these three kinds of remote sensing data for LAI retrieval was assessed according to the estimation accuracy of models. The experimental results showed that the models based on the ground hyperspectral and UAV multispectral data got better estimation accuracy (R² was more than 0.69 and RMSE was less than 0.4 at 0.01 significance level), compared with the model based on WFV data. The RVI logarithmic model based on ground hyperspectral data was little superior to the NDVI linear model based on UAV multispectral data (The difference in E(A), R² and RMSE were 0.3%, 0.04 and 0.006, respectively). The models based on WFV data got the lowest estimation accuracy with R2 less than 0.30 and RMSE more than 0.70. The effects of sensor spectral response characteristics, sensor geometric location and spatial resolution on the soybean LAI retrieval were discussed. The results demonstrated that ground hyperspectral data were advantageous but not prominent over traditional multispectral data in soybean LAI retrieval. WFV imagery with 16 m spatial resolution could not meet the requirements of crop growth monitoring at field scale. Under the condition of ensuring the high precision in retrieving soybean LAI and working efficiently, the approach to acquiring agricultural information by UAV remote sensing could yet be regarded as an optimal plan. Therefore, in the case of more and more available remote sensing information sources, agricultural UAV remote sensing could become an important information resource for guiding field-scale crop management and provide more scientific and accurate information for precision agriculture research.

Seasonal associations and atmospheric transport distances of fungi in the genus Fusarium collected with unmanned aerial vehicles and ground-based sampling devices

NASA Astrophysics Data System (ADS)

Lin, Binbin; Ross, Shane D.; Prussin, Aaron J.; Schmale, David G.

2014-09-01

Spores of fungi in the genus Fusarium may be transported through the atmosphere over long distances. New information is needed to characterize seasonal trends in atmospheric loads of Fusarium and to pinpoint the source(s) of inoculum at both local (farm) and regional (state or country) scales. We hypothesized that (1) atmospheric concentrations of Fusarium spores in an agricultural ecosystem vary with height and season and (2) transport distances from potential inoculum source(s) vary with season. To test these hypotheses, spores of Fusarium were collected from the atmosphere in an agricultural ecosystem in Blacksburg, VA, USA using a Burkard volumetric sampler (BVS) 1 m above ground level and autonomous unmanned aerial vehicles (UAVs) 100 m above ground level. More than 2200 colony forming units (CFUs) of Fusarium were collected during 104 BVS sampling periods and 180 UAV sampling periods over four calendar years (2009-2012). Spore concentrations ranged from 0 to 13 and 0 to 23 spores m-3 for the BVS and the UAVs, respectively. Spore concentrations were generally higher in the fall, spring, and summer, and lower in the winter. Spore concentrations from the BVS were generally higher than those from the UAVs for both seasonal and hourly collections. A Gaussian plume transport model was used to estimate distances to the potential inoculum source(s) by season, and produced mean transport distances of 1.4 km for the spring, 1.7 km for the summer, 1.2 km for the fall, and 4.1 km for the winter. Environmental signatures that predict atmospheric loads of Fusarium could inform disease spread, air pollution, and climate change.

An evaluation of a UAV guidance system with consumer grade GPS receivers

NASA Astrophysics Data System (ADS)

Rosenberg, Abigail Stella

Remote sensing has been demonstrated an important tool in agricultural and natural resource management and research applications, however there are limitations that exist with traditional platforms (i.e., hand held sensors, linear moves, vehicle mounted, airplanes, remotely piloted vehicles (RPVs), unmanned aerial vehicles (UAVs) and satellites). Rapid technological advances in electronics, computers, software applications, and the aerospace industry have dramatically reduced the cost and increased the availability of remote sensing technologies. Remote sensing imagery vary in spectral, spatial, and temporal resolutions and are available from numerous providers. Appendix A presented results of a test project that acquired high-resolution aerial photography with a RPV to map the boundary of a 0.42 km2 fire area. The project mapped the boundaries of the fire area from a mosaic of the aerial images collected and compared this with ground-based measurements. The project achieved a 92.4% correlation between the aerial assessment and the ground truth data. Appendix B used multi-objective analysis to quantitatively assess the tradeoffs between different sensor platform attributes to identify the best overall technology. Experts were surveyed to identify the best overall technology at three different pixel sizes. Appendix C evaluated the positional accuracy of a relatively low cost UAV designed for high resolution remote sensing of small areas in order to determine the positional accuracy of sensor readings. The study evaluated the accuracy and uncertainty of a UAV flight route with respect to the programmed waypoints and of the UAV's GPS position, respectively. In addition, the potential displacement of sensor data was evaluated based on (1) GPS measurements on board the aircraft and (2) the autopilot's circuit board with 3-axis gyros and accelerometers (i.e., roll, pitch, and yaw). The accuracies were estimated based on a 95% confidence interval or similar methods. The accuracy achieved in the second and third manuscripts demonstrates that reasonably priced, high resolution remote sensing via RPVs and UAVs is practical for agriculture and natural resource professionals.

Mission Planning for Tactical Aircraft (Preflight and In-Flight) (Systemes de Planification des Missions Pour Avions Tactiques) (Avant Vol et en Vol).

DTIC Science & Technology

1992-12-01

Ground-Based Mission Planning Systems 9 2.3 Networking Mission Planning Systems 11 2.4 Fully Automated Mission Planning I I 2.5 Unmanned Air Vehicles 13...Missile Engagement Zone RPV Remotely Piloted Vehicle MIDS Multifunction Information Distribution System RRDB Rapidly Reconfigurable Databus MIL-STD...Comrmantd OPORD Operations Order TV Television OPS Operational OR Operational Relationship UAV Unmanned Air Vehicle UAV Unnmanned Air Vehicle PA

Surface target-tracking guidance by self-organizing formation flight of fixed-wing UAV

NASA Astrophysics Data System (ADS)

Regina, N.; Zanzi, M.

This paper presents a new concept of ground target surveillance based on a formation flight of two Unmanned Aerial Vehicles (UAVs) of fixed-wing type. Each UAV considered in this work has its own guidance law specifically designed for two different aims. A self organizing non-symmetric collaborative surveying scheme has been developed based on pursuers with different roles: the close-up-pursuer and the distance-pursuer. The close-up-pursuer behaves according to a guidance law which takes it to continually over-fly the target, also optimizing flight endurance. On the other hand, the distancepursuer behaves so as to circle around the target by flying at a certain distance and altitude from it; moreover, its motion ensures the maximum “ seeability” of the ground based target. In addition, the guidance law designed for the distance-pursuer also implements a collision avoidance feature in order to prevent possible risks of collision with the close-up-pursuer during the tracking maneuvers. The surveying scheme is non-symmetric in the sense that the collision avoidance feature is accomplished by a guidance law implemented only on one of the two pursuers; moreover, it is collaborative because the surveying is performed by different tasks of two UAVs and is self-organizing because, due to the collision avoidance feature, target tracking does not require pre-planned collision-risk-free trajectories but trajectories are generated in real time.

DAZZLE project: UAV to ground communication system using a laser and a modulated retro-reflector

NASA Astrophysics Data System (ADS)

Thueux, Yoann; Avlonitis, Nicholas; Erry, Gavin

2014-10-01

The advent of the Unmanned Aerial Vehicle (UAV) has generated the need for reduced size, weight and power (SWaP) requirements for communications systems with a high data rate, enhanced security and quality of service. This paper presents the current results of the DAZZLE project run by Airbus Group Innovations. The specifications, integration steps and initial performance of a UAV to ground communication system using a laser and a modulated retro-reflector are detailed. The laser operates at the wavelength of 1550nm and at power levels that keep it eye safe. It is directed using a FLIR pan and tilt unit driven by an image processing-based system that tracks the UAV in flight at a range of a few kilometers. The modulated retro-reflector is capable of a data rate of 20Mbps over short distances, using 200mW of electrical power. The communication system was tested at the Pershore Laser Range in July 2014. Video data from a flying Octocopter was successfully transmitted over 1200m. During the next phase of the DAZZLE project, the team will attempt to produce a modulated retro-reflector capable of 1Gbps in partnership with the research institute Acreo1 based in Sweden. A high speed laser beam steering capability based on a Spatial Light Modulator will also be added to the system to improve beam pointing accuracy.

Implementation of high-gain observer on low-cost fused IR-OS sensor embedded in UAV system

NASA Astrophysics Data System (ADS)

Nor, E. Mohd; Noor, S. B. Mohd; Bahiki, M. R.; Azrad, S.

2017-12-01

This paper presents discrete time implementation of a high gain observer (HGO) and extended term to estimate the state velocity and acceleration from the position measured by a low-cost sensor installed on-board the unmanned aerial vehicle (UAV). Owing to the low-cost sensor, the signal produced from fused IR-OS is noisy and therefore, additional filters are used to remove the noise. This study proposes an alternative to this standard and tedious procedure using HGO. The discrete time implementation of HGO and its extended term is presented and ground tests are conducted to verify the algorithm by inducing a dynamic motion on the UAV platform embedded with the fusion IR-OS onboard. A comparison study is conducted using standard numerical differentiation and ground truth measurement by OptiTrack. The results show that EHGO can produce a velocity signal with the same quality as that of differentiated signal from fused IR-OS using Kalman filter. The novelty of HGO lies in its simplicity and its minimal tuning of parameters.

Guidance and Control of a Small Unmanned Aerial Vehicle and Autonomous Flight Experiments

NASA Astrophysics Data System (ADS)

Fujinaga, Jin; Tokutake, Hiroshi; Sunada, Shigeru

This paper describes the development of a fixed-wing small-size UAV and the design of its flight controllers. The developed UAV’s wing span is 0.6m, and gross weight is 0.27kg. In order to ensure robust performances of the longitudinal and lateral-directional motions of the UAV, flight controllers are designed for these motions with μ-synthesis. Numerical simulations show that the designed controllers attain good robust stabilities and performances, and have good tracking performance for command. After an order-reduction and discretization, the designed flight controllers were implemented in the UAV. A flight test was performed, and the ability of the UAV to fly autonomously, passing over waypoints, was demonstrated.

Image-based tracking and sensor resource management for UAVs in an urban environment

NASA Astrophysics Data System (ADS)

Samant, Ashwin; Chang, K. C.

2010-04-01

Coordination and deployment of multiple unmanned air vehicles (UAVs) requires a lot of human resources in order to carry out a successful mission. The complexity of such a surveillance mission is significantly increased in the case of an urban environment where targets can easily escape from the UAV's field of view (FOV) due to intervening building and line-of-sight obstruction. In the proposed methodology, we focus on the control and coordination of multiple UAVs having gimbaled video sensor onboard for tracking multiple targets in an urban environment. We developed optimal path planning algorithms with emphasis on dynamic target prioritizations and persistent target updates. The command center is responsible for target prioritization and autonomous control of multiple UAVs, enabling a single operator to monitor and control a team of UAVs from a remote location. The results are obtained using extensive 3D simulations in Google Earth using Tangent plus Lyapunov vector field guidance for target tracking.

UAV Flight Control Using Distributed Actuation and Sensing

NASA Technical Reports Server (NTRS)

Barnwell, William G.; Heinzen, Stearns N.; Hall, Charles E., Jr.; Chokani, Ndaona; Raney, David L. (Technical Monitor)

2003-01-01

An array of effectors and sensors has been designed, tested and implemented on a Blended Wing Body Uninhabited Aerial Vehicle (UAV). This UAV is modified to serve as a flying, controls research, testbed. This effectorhensor array provides for the dynamic vehicle testing of controller designs and the study of decentralized control techniques. Each wing of the UAV is equipped with 12 distributed effectors that comprise a segmented array of independently actuated, contoured control surfaces. A single pressure sensor is installed near the base of each effector to provide a measure of deflections of the effectors. The UAV wings were tested in the North Carolina State University Subsonic Wind Tunnel and the pressure distribution that result from the deflections of the effectors are characterized. The results of the experiments are used to develop a simple, but accurate, prediction method, such that for any arrangement of the effector array the corresponding pressure distribution can be determined. Numerical analysis using the panel code CMARC verifies this prediction method.

Quality Analysis on 3d Buidling Models Reconstructed from Uav Imagery

NASA Astrophysics Data System (ADS)

Jarzabek-Rychard, M.; Karpina, M.

2016-06-01

Recent developments in UAV technology and structure from motion techniques have effected that UAVs are becoming standard platforms for 3D data collection. Because of their flexibility and ability to reach inaccessible urban parts, drones appear as optimal solution for urban applications. Building reconstruction from the data collected with UAV has the important potential to reduce labour cost for fast update of already reconstructed 3D cities. However, especially for updating of existing scenes derived from different sensors (e.g. airborne laser scanning), a proper quality assessment is necessary. The objective of this paper is thus to evaluate the potential of UAV imagery as an information source for automatic 3D building modeling at LOD2. The investigation process is conducted threefold: (1) comparing generated SfM point cloud to ALS data; (2) computing internal consistency measures of the reconstruction process; (3) analysing the deviation of Check Points identified on building roofs and measured with a tacheometer. In order to gain deep insight in the modeling performance, various quality indicators are computed and analysed. The assessment performed according to the ground truth shows that the building models acquired with UAV-photogrammetry have the accuracy of less than 18 cm for the plannimetric position and about 15 cm for the height component.

Volumetric calculation using low cost unmanned aerial vehicle (UAV) approach

NASA Astrophysics Data System (ADS)

Rahman, A. A. Ab; Maulud, K. N. Abdul; Mohd, F. A.; Jaafar, O.; Tahar, K. N.

2017-12-01

Unmanned Aerial Vehicles (UAV) technology has evolved dramatically in the 21st century. It is used by both military and general public for recreational purposes and mapping work. Operating cost for UAV is much cheaper compared to that of normal aircraft and it does not require a large work space. The UAV systems have similar functions with the LIDAR and satellite images technologies. These systems require a huge cost, labour and time consumption to produce elevation and dimension data. Measurement of difficult objects such as water tank can also be done by using UAV. The purpose of this paper is to show the capability of UAV to compute the volume of water tank based on a different number of images and control points. The results were compared with the actual volume of the tank to validate the measurement. In this study, the image acquisition was done using Phantom 3 Professional, which is a low cost UAV. The analysis in this study is based on different volume computations using two and four control points with variety set of UAV images. The results show that more images will provide a better quality measurement. With 95 images and four GCP, the error percentage to the actual volume is about 5%. Four controls are enough to get good results but more images are needed, estimated about 115 until 220 images. All in all, it can be concluded that the low cost UAV has a potential to be used for volume of water and dimension measurement.

Networking Multiple Autonomous Air and Ocean Vehicles for Oceanographic Research and Monitoring

NASA Astrophysics Data System (ADS)

McGillivary, P. A.; Borges de Sousa, J.; Rajan, K.

2013-12-01

Autonomous underwater and surface vessels (AUVs and ASVs) are coming into wider use as components of oceanographic research, including ocean observing systems. Unmanned airborne vehicles (UAVs) are now available at modest cost, allowing multiple UAVs to be deployed with multiple AUVs and ASVs. For optimal use good communication and coordination among vehicles is essential. We report on the use of multiple AUVs networked in communication with multiple UAVs. The UAVs are augmented by inferential reasoning software developed at MBARI that allows UAVs to recognize oceanographic fronts and change their navigation and control. This in turn allows UAVs to automatically to map frontal features, as well as to direct AUVs and ASVs to proceed to such features and conduct sampling via onboard sensors to provide validation for airborne mapping. ASVs can also act as data nodes for communication between UAVs and AUVs, as well as collecting data from onboard sensors, while AUVs can sample the water column vertically. This allows more accurate estimation of phytoplankton biomass and productivity, and can be used in conjunction with UAV sampling to determine air-sea flux of gases (e.g. CO2, CH4, DMS) affecting carbon budgets and atmospheric composition. In particular we describe tests in July 2013 conducted off Sesimbra, Portugal in conjunction with the Portuguese Navy by the University of Porto and MBARI with the goal of tracking large fish in the upper water column with coordinated air/surface/underwater measurements. A thermal gradient was observed in the infrared by a low flying UAV, which was used to dispatch an AUV to obtain ground truth to demonstrate the event-response capabilities using such autonomous platforms. Additional field studies in the future will facilitate integration of multiple unmanned systems into research vessel operations. The strength of hardware and software tools described in this study is to permit fundamental oceanographic measurements of both ocean and atmosphere over temporal and spatial scales that have previously been problematic. The methods demonstrated are particularly suited to the study of oceanographic fronts and for tracking and mapping oil spills or plankton blooms. With the networked coordination of multiple autonomous systems, individual components may be changed out while ocean observations continue, allowing coarse to fine spatial studies of hydrographic features over temporal dimensions that would otherwise be difficult, including diurnal and tidal periods. Constraints on these methods currently involve coordination of data archiving systems into shipboard operating systems, familiarization of oceanographers with these methods, and existing nearshore airspace use constraints on UAVs. An important outcome of these efforts is to understand the methodology for using multiple heterogeneous autonomous vehicles for targeted science exploration.

Applications of UAVs for Remote Sensing of Critical Infrastructure

NASA Technical Reports Server (NTRS)

Wegener, Steve; Brass, James; Schoenung, Susan

2003-01-01

The surveillance of critical facilities and national infrastructure such as waterways, roadways, pipelines and utilities requires advanced technological tools to provide timely, up to date information on structure status and integrity. Unmanned Aerial Vehicles (UAVs) are uniquely suited for these tasks, having large payload and long duration capabilities. UAVs also have the capability to fly dangerous and dull missions, orbiting for 24 hours over a particular area or facility providing around the clock surveillance with no personnel onboard. New UAV platforms and systems are becoming available for commercial use. High altitude platforms are being tested for use in communications, remote sensing, agriculture, forestry and disaster management. New payloads are being built and demonstrated onboard the UAVs in support of these applications. Smaller, lighter, lower power consumption imaging systems are currently being tested over coffee fields to determine yield and over fires to detect fire fronts and hotspots. Communication systems that relay video, meteorological and chemical data via satellite to users on the ground in real-time have also been demonstrated. Interest in this technology for infrastructure characterization and mapping has increased dramatically in the past year. Many of the UAV technological developments required for resource and disaster monitoring are being used for the infrastructure and facility mapping activity. This paper documents the unique contributions from NASA;s Environmental Research Aircraft and Sensor Technology (ERAST) program to these applications. ERAST is a UAV technology development effort by a consortium of private aeronautical companies and NASA. Details of demonstrations of UAV capabilities currently underway are also presented.

Atmospheric Profiles, Clouds and the Evolution of Sea Ice Cover in the Beaufort and Chukchi Seas

DTIC Science & Technology

2013-09-30

by incorporating the proposed IR sensors and ground­sky temperature difference algorithm into a tethered balloon borne payload (Figure 6).This...a drop or balloon sonde, which is low cost but cannot be guided, and a typical UAV, which provides guidance flexibility but uses costly avionics and...air space using balloon launches The SmartSonde vehicle was first test flown under a bungee launch system and manual (R/C) control. After several

Demonstration of UAV deployment and control of mobile wireless sensing networks for modal analysis of structures

NASA Astrophysics Data System (ADS)

Zhou, Hao; Hirose, Mitsuhito; Greenwood, William; Xiao, Yong; Lynch, Jerome; Zekkos, Dimitrios; Kamat, Vineet

2016-04-01

Unmanned aerial vehicles (UAVs) can serve as a powerful mobile sensing platform for assessing the health of civil infrastructure systems. To date, the majority of their uses have been dedicated to vision and laser-based spatial imaging using on-board cameras and LiDAR units, respectively. Comparatively less work has focused on integration of other sensing modalities relevant to structural monitoring applications. The overarching goal of this study is to explore the ability for UAVs to deploy a network of wireless sensors on structures for controlled vibration testing. The study develops a UAV platform with an integrated robotic gripper that can be used to install wireless sensors in structures, drop a heavy weight for the introduction of impact loads, and to uninstall wireless sensors for reinstallation elsewhere. A pose estimation algorithm is embedded in the UAV to estimate the location of the UAV during sensor placement and impact load introduction. The Martlet wireless sensor network architecture is integrated with the UAV to provide the UAV a mobile sensing capability. The UAV is programmed to command field deployed Martlets, aggregate and temporarily store data from the wireless sensor network, and to communicate data to a fixed base station on site. This study demonstrates the integrated UAV system using a simply supported beam in the lab with Martlet wireless sensors placed by the UAV and impact load testing performed. The study verifies the feasibility of the integrated UAV-wireless monitoring system architecture with accurate modal characteristics of the beam estimated by modal analysis.

UAV Control on the Basis of 3D Landmark Bearing-Only Observations.

PubMed

Karpenko, Simon; Konovalenko, Ivan; Miller, Alexander; Miller, Boris; Nikolaev, Dmitry

2015-11-27

The article presents an approach to the control of a UAV on the basis of 3D landmark observations. The novelty of the work is the usage of the 3D RANSAC algorithm developed on the basis of the landmarks' position prediction with the aid of a modified Kalman-type filter. Modification of the filter based on the pseudo-measurements approach permits obtaining unbiased UAV position estimation with quadratic error characteristics. Modeling of UAV flight on the basis of the suggested algorithm shows good performance, even under significant external perturbations.

Neural network-based optimal adaptive output feedback control of a helicopter UAV.

PubMed

Nodland, David; Zargarzadeh, Hassan; Jagannathan, Sarangapani

2013-07-01

Helicopter unmanned aerial vehicles (UAVs) are widely used for both military and civilian operations. Because the helicopter UAVs are underactuated nonlinear mechanical systems, high-performance controller design for them presents a challenge. This paper introduces an optimal controller design via an output feedback for trajectory tracking of a helicopter UAV, using a neural network (NN). The output-feedback control system utilizes the backstepping methodology, employing kinematic and dynamic controllers and an NN observer. The online approximator-based dynamic controller learns the infinite-horizon Hamilton-Jacobi-Bellman equation in continuous time and calculates the corresponding optimal control input by minimizing a cost function, forward-in-time, without using the value and policy iterations. Optimal tracking is accomplished by using a single NN utilized for the cost function approximation. The overall closed-loop system stability is demonstrated using Lyapunov analysis. Finally, simulation results are provided to demonstrate the effectiveness of the proposed control design for trajectory tracking.

Adaptive sliding mode control for finite-time stability of quad-rotor UAVs with parametric uncertainties.

PubMed

Mofid, Omid; Mobayen, Saleh

2018-01-01

Adaptive control methods are developed for stability and tracking control of flight systems in the presence of parametric uncertainties. This paper offers a design technique of adaptive sliding mode control (ASMC) for finite-time stabilization of unmanned aerial vehicle (UAV) systems with parametric uncertainties. Applying the Lyapunov stability concept and finite-time convergence idea, the recommended control method guarantees that the states of the quad-rotor UAV are converged to the origin with a finite-time convergence rate. Furthermore, an adaptive-tuning scheme is advised to guesstimate the unknown parameters of the quad-rotor UAV at any moment. Finally, simulation results are presented to exhibit the helpfulness of the offered technique compared to the previous methods. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

High-speed optical links for UAV applications

NASA Astrophysics Data System (ADS)

Chen, C.; Grier, A.; Malfa, M.; Booen, E.; Harding, H.; Xia, C.; Hunwardsen, M.; Demers, J.; Kudinov, K.; Mak, G.; Smith, B.; Sahasrabudhe, A.; Patawaran, F.; Wang, T.; Wang, A.; Zhao, C.; Leang, D.; Gin, J.; Lewis, M.; Nguyen, D.; Quirk, K.

2017-02-01

High speed optical backbone links between a fleet of UAVs is an integral part of the Facebook connectivity architecture. To support the architecture, the optical terminals need to provide high throughput rates (in excess of tens of Gbps) while achieving low weight and power consumption. The initial effort is to develop and demonstrate an optical terminal capable of meeting the data rate requirements and demonstrate its functions for both air-air and air-ground engagements. This paper is a summary of the effort to date.

Development of a Novel, Two-Processor Architecture for a Small UAV Autopilot System,

DTIC Science & Technology

2006-07-26

is, and the control laws the user implements to control it. The flight control system board will contain the processor selected for this system...Unit (IMU). The IMU contains solid-state gyros and accelerometers and uses these to determine the attitude of the UAV within the three dimensions of...multiple-UAV swarming for combat support operations. The mission processor board will contain the processor selected to execute the mission

Development of a bio-inspired UAV perching system

NASA Astrophysics Data System (ADS)

Xie, Pu

Although technologies of unmanned aerial vehicles (UAVs) including micro air vehicles (MAVs) have been greatly advanced in the recent years, it is still very difficult for a UAV to perform some very challenging tasks such as perching to any desired spot reliably and agilely like a bird. Unlike the UAVs, the biological control mechanism of birds has been optimized through millions of year evolution and hence, they can perform many extremely maneuverability tasks, such as perching or grasping accurately and robustly. Therefore, we have good reason to learn from the nature in order to significantly improve the capabilities of UAVs. The development of a UAV perching system is becoming feasible, especially after a lot of research contributions in ornithology which involve the analysis of the bird's functionalities. Meanwhile, as technology advances in many engineering fields, such as airframes, propulsion, sensors, batteries, micro-electromechanical-system (MEMS), and UAV technology is also advancing rapidly. All of these research efforts in ornithology and the fast growing development technologies in UAV applications are motivating further interests and development in the area of UAV perching and grasping research. During the last decade, the research contributions about UAV perching and grasping were mainly based on fixed-wing, flapping-wing, and rotorcraft UAVs. However, most of the current researches in UAV systems with perching and grasping capability are focusing on either active (powered) grasping and perching or passive (unpowered) perching. Although birds do have both active and passive perching capabilities depending on their needs, there is no UAV perching system with both capabilities. In this project, we focused on filling this gap. Inspired by the anatomy analysis of bird legs and feet, a novel perching system has been developed to implement the bionics action for both active grasping and passive perching. In addition, for developing a robust and autonomous perching system, the following objectives were included for this project. The statics model was derived through both quasi-static and analytical method. The grasping stable condition and grasping target of the mechanical gripper were studied through the static analysis. Furthermore, the contact behavior between each foot and the perched object was modeled and evaluated on SimMechanics based on the contact force model derived through virtual principle. The kinematics modeling of UAV perching system was governed with Euler angles and quaternions. Also the propulsion model of the brushless motors was introduced and calibrated. In addition, the flight dynamics model of the UAV system was developed for simulation-based analysis prior to developing a hardware prototype and flight experiment. A special inertial measurement unit (IMU) was designed which has the capability of indirectly calculating the angular acceleration from the angular velocity and the linear acceleration readings. Moreover, a commercial-of-the-shelf (COTS) autopilot-APM 2.6 was selected for the autonomous flight control of the quadrotor. The APM 2.6 is a complete open source autopilot system, which allows the user to turn any fixed, rotary wing or multi-rotor vehicle into a fully autonomous vehicle and capable of performing programmed GPS missions with pre-programed waypoints. In addition, algorithms for inverted pendulum control and autonomous perching control was introduced. The proportion-integrate-differential (PID) controller was used for the simplified UAV perching with inverted pendulum model for horizontal balance. The performance of the controller was verified through both simulation and experiment. In addition, for the purpose of achieving the autonomous perching, guidance and control algorithms were developed the UAV perching system. For guidance, the desired flight trajectory was developed based on a bio-behavioral tau theory which was established from studying the natural motion patterns of animals and human arms approaching to a fixed or moving target for grasping or capturing. The autonomous flight control was also implemented through a PID controller. Autonomous flight performance was proved through simulation in SimMechanics. Finally, the prototyping of our designs were conducted in different generations of our bio-inspired UAV perching system, which include the leg prototype, gripper prototype, and system prototype. Both the machined prototype and 3D printed prototype were tried. The performance of these prototypes was tested through experiments.

Unmanned Aerial Vehicle to Estimate Nitrogen Status of Turfgrasses

PubMed Central

Corniglia, Matteo; Gaetani, Monica; Grossi, Nicola; Magni, Simone; Migliazzi, Mauro; Angelini, Luciana; Mazzoncini, Marco; Silvestri, Nicola; Fontanelli, Marco; Raffaelli, Michele; Peruzzi, Andrea; Volterrani, Marco

2016-01-01

Spectral reflectance data originating from Unmanned Aerial Vehicle (UAV) imagery is a valuable tool to monitor plant nutrition, reduce nitrogen (N) application to real needs, thus producing both economic and environmental benefits. The objectives of the trial were i) to compare the spectral reflectance of 3 turfgrasses acquired via UAV and by a ground-based instrument; ii) to test the sensitivity of the 2 data acquisition sources in detecting induced variation in N levels. N application gradients from 0 to 250 kg ha-1 were created on 3 different turfgrass species: Cynodon dactylon x transvaalensis (Cdxt) ‘Patriot’, Zoysia matrella (Zm) ‘Zeon’ and Paspalum vaginatum (Pv) ‘Salam’. Proximity and remote-sensed reflectance measurements were acquired using a GreenSeeker handheld crop sensor and a UAV with onboard a multispectral sensor, to determine Normalized Difference Vegetation Index (NDVI). Proximity-sensed NDVI is highly correlated with data acquired from UAV with r values ranging from 0.83 (Zm) to 0.97 (Cdxt). Relating NDVI-UAV with clippings N, the highest r is for Cdxt (0.95). The most reactive species to N fertilization is Cdxt with a clippings N% ranging from 1.2% to 4.1%. UAV imagery can adequately assess the N status of turfgrasses and its spatial variability within a species, so for large areas, such as golf courses, sod farms or race courses, UAV acquired data can optimize turf management. For relatively small green areas, a hand-held crop sensor can be a less expensive and more practical option. PMID:27341674

Integrating critical interface elements for intuitive single-display aviation control of UAVs

NASA Astrophysics Data System (ADS)

Cooper, Joseph L.; Goodrich, Michael A.

2006-05-01

Although advancing levels of technology allow UAV operators to give increasingly complex commands with expanding temporal scope, it is unlikely that the need for immediate situation awareness and local, short-term flight adjustment will ever be completely superseded. Local awareness and control are particularly important when the operator uses the UAV to perform a search or inspection task. There are many different tasks which would be facilitated by search and inspection capabilities of a camera-equipped UAV. These tasks range from bridge inspection and news reporting to wilderness search and rescue. The system should be simple, inexpensive, and intuitive for non-pilots. An appropriately designed interface should (a) provide a context for interpreting video and (b) support UAV tasking and control, all within a single display screen. In this paper, we present and analyze an interface that attempts to accomplish this goal. The interface utilizes a georeferenced terrain map rendered from publicly available altitude data and terrain imagery to create a context in which the location of the UAV and the source of the video are communicated to the operator. Rotated and transformed imagery from the UAV provides a stable frame of reference for the operator and integrates cleanly into the terrain model. Simple icons overlaid onto the main display provide intuitive control and feedback when necessary but fade to a semi-transparent state when not in use to avoid distracting the operator's attention from the video signal. With various interface elements integrated into a single display, the interface runs nicely on a small, portable, inexpensive system with a single display screen and simple input device, but is powerful enough to allow a single operator to deploy, control, and recover a small UAV when coupled with appropriate autonomy. As we present elements of the interface design, we will identify concepts that can be leveraged into a large class of UAV applications.

On decentralized adaptive full-order sliding mode control of multiple UAVs.

PubMed

Xiang, Xianbo; Liu, Chao; Su, Housheng; Zhang, Qin

2017-11-01

In this study, a novel decentralized adaptive full-order sliding mode control framework is proposed for the robust synchronized formation motion of multiple unmanned aerial vehicles (UAVs) subject to system uncertainty. First, a full-order sliding mode surface in a decentralized manner is designed to incorporate both the individual position tracking error and the synchronized formation error while the UAV group is engaged in building a certain desired geometric pattern in three dimensional space. Second, a decentralized virtual plant controller is constructed which allows the embedded low-pass filter to attain the chattering free property of the sliding mode controller. In addition, robust adaptive technique is integrated in the decentralized chattering free sliding control design in order to handle unknown bounded uncertainties, without requirements for assuming a priori knowledge of bounds on the system uncertainties as stated in conventional chattering free control methods. Subsequently, system robustness as well as stability of the decentralized full-order sliding mode control of multiple UAVs is synthesized. Numerical simulation results illustrate the effectiveness of the proposed control framework to achieve robust 3D formation flight of the multi-UAV system. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

The Use of Drones in Spain: Towards a Platform for Controlling UAVs in Urban Environments

PubMed Central

Bueno De Mata, Federico

2018-01-01

Rapid advances in technology make it necessary to prepare our society in every aspect. Some of the most significant technological developments of the last decade are the UAVs (Unnamed Aerial Vehicles) or drones. UAVs provide a wide range of new possibilities and have become a tool that we now use on a daily basis. However, if their use is not controlled, it could entail several risks, which make it necessary to legislate and monitor UAV flights to ensure, inter alia, the security and privacy of all citizens. As a result of this problem, several laws have been passed which seek to regulate their use; however, no proposals have been made with regards to the control of airspace from a technological point of view. This is exactly what we propose in this article: a platform with different modes designed to control UAVs and monitor their status. The features of the proposed platform provide multiple advantages that make the use of UAVs more secure, such as prohibiting UAVs’ access to restricted areas or avoiding collisions between vehicles. The platform has been successfully tested in Salamanca, Spain. PMID:29751554

Development and Evaluation of a UAV-Photogrammetry System for Precise 3D Environmental Modeling.

PubMed

Shahbazi, Mozhdeh; Sohn, Gunho; Théau, Jérôme; Menard, Patrick

2015-10-30

The specific requirements of UAV-photogrammetry necessitate particular solutions for system development, which have mostly been ignored or not assessed adequately in recent studies. Accordingly, this paper presents the methodological and experimental aspects of correctly implementing a UAV-photogrammetry system. The hardware of the system consists of an electric-powered helicopter, a high-resolution digital camera and an inertial navigation system. The software of the system includes the in-house programs specifically designed for camera calibration, platform calibration, system integration, on-board data acquisition, flight planning and on-the-job self-calibration. The detailed features of the system are discussed, and solutions are proposed in order to enhance the system and its photogrammetric outputs. The developed system is extensively tested for precise modeling of the challenging environment of an open-pit gravel mine. The accuracy of the results is evaluated under various mapping conditions, including direct georeferencing and indirect georeferencing with different numbers, distributions and types of ground control points. Additionally, the effects of imaging configuration and network stability on modeling accuracy are assessed. The experiments demonstrated that 1.55 m horizontal and 3.16 m vertical absolute modeling accuracy could be achieved via direct geo-referencing, which was improved to 0.4 cm and 1.7 cm after indirect geo-referencing.

Development and Evaluation of a UAV-Photogrammetry System for Precise 3D Environmental Modeling

PubMed Central

Shahbazi, Mozhdeh; Sohn, Gunho; Théau, Jérôme; Menard, Patrick

2015-01-01

The specific requirements of UAV-photogrammetry necessitate particular solutions for system development, which have mostly been ignored or not assessed adequately in recent studies. Accordingly, this paper presents the methodological and experimental aspects of correctly implementing a UAV-photogrammetry system. The hardware of the system consists of an electric-powered helicopter, a high-resolution digital camera and an inertial navigation system. The software of the system includes the in-house programs specifically designed for camera calibration, platform calibration, system integration, on-board data acquisition, flight planning and on-the-job self-calibration. The detailed features of the system are discussed, and solutions are proposed in order to enhance the system and its photogrammetric outputs. The developed system is extensively tested for precise modeling of the challenging environment of an open-pit gravel mine. The accuracy of the results is evaluated under various mapping conditions, including direct georeferencing and indirect georeferencing with different numbers, distributions and types of ground control points. Additionally, the effects of imaging configuration and network stability on modeling accuracy are assessed. The experiments demonstrated that 1.55 m horizontal and 3.16 m vertical absolute modeling accuracy could be achieved via direct geo-referencing, which was improved to 0.4 cm and 1.7 cm after indirect geo-referencing. PMID:26528976

Land Survey from Unmaned Aerial Veichle

NASA Astrophysics Data System (ADS)

Peterman, V.; Mesarič, M.

2012-07-01

In this paper we present, how we use a quadrocopter unmanned aerial vehicle with a camera attached to it, to do low altitude photogrammetric land survey. We use the quadrocopter to take highly overlapping photos of the area of interest. A "structure from motion" algorithm is implemented to get parameters of camera orientations and to generate a sparse point cloud representation of objects in photos. Than a patch based multi view stereo algorithm is applied to generate a dense point cloud. Ground control points are used to georeference the data. Further processing is applied to generate digital orthophoto maps, digital surface models, digital terrain models and assess volumes of various types of material. Practical examples of land survey from a UAV are presented in the paper. We explain how we used our system to monitor the reconstruction of commercial building, then how our UAV was used to assess the volume of coal supply for Ljubljana heating plant. Further example shows the usefulness of low altitude photogrammetry for documentation of archaeological excavations. In the final example we present how we used our UAV to prepare an underlay map for natural gas pipeline's route planning. In the final analysis we conclude that low altitude photogrammetry can help bridge the gap between laser scanning and classic tachymetric survey, since it offers advantages of both techniques.

Thermal Imaging of Subsurface Coal Fires by means of an Unmanned Aerial Vehicle (UAV) in the Autonomous Province Xinjiang, PRC

NASA Astrophysics Data System (ADS)

Vasterling, Margarete; Schloemer, Stefan; Fischer, Christian; Ehrler, Christoph

2010-05-01

Spontaneous combustion of coal and resulting coal fires lead to very high temperatures in the subsurface. To a large amount the heat is transferred to the surface by convective and conductive transport inducing a more or less pronounced thermal anomaly. During the past decade satellite-based infrared-imaging (ASTER, MODIS) was the method of choice for coal fire detection on a local and regional scale. However, the resolution is by far too low for a detailed analysis of single coal fires which is essential prerequisite for corrective measures (i.e. fire fighting) and calculation of carbon dioxide emission based on a complex correlation between energy release and CO2 generation. Consequently, within the framework of the Sino-German research project "Innovative Technologies for Exploration, Extinction and Monitoring of Coal Fires in Northern China", a new concept was developed and successfully tested. An unmanned aerial vehicle (UAV) was equipped with a lightweight camera for thermografic (resolution 160 by 120 pixel, dynamic range -20 to 250°C) and for visual imaging. The UAV designed as an octocopter is able to hover at GPS controlled waypoints during predefined flight missions. The application of a UAV has several advantages. Compared to point measurements on the ground the thermal imagery quickly provides the spatial distribution of the temperature anomaly with a much better resolution. Areas otherwise not accessible (due to topography, fire induced cracks, etc.) can easily be investigated. The results of areal surveys on two coal fires in Xinjiang are presented. Georeferenced thermal and visual images were mosaicked together and analyzed. UAV-born data do well compared to temperatures measured directly on the ground and cover large areas in detail. However, measuring surface temperature alone is not sufficient. Simultaneous measurements made at the surface and in roughly 15cm depth proved substantial temperature gradients in the upper soil. Thus the temperature measured at the surface underestimates the energy emitted by the subsurface coal fire. In addition, surface temperature is strongly influenced by solar radiation and the prevailing ambient conditions (wind, temperature, humidity). As a consequence there is no simple correlation between surface and subsurface soil temperature. Efforts have been made to set up a coupled energy transport and energy balance model for the near surface considering thermal conduction, solar irradiation, thermal radiative energy and ambient temperature so far. The model can help to validate space-born and UAV-born thermal imagery and link surface to subsurface temperature but depends on in-situ measurements for input parameter determination and calibration. Results obtained so far strongly necessitate the integration of different data sources (in-situ / remote; point / area; local / medium scale) to obtain a reliable energy release estimation which is then used for coal fire characterization.

Pricise Target Geolocation Based on Integeration of Thermal Video Imagery and Rtk GPS in Uavs

NASA Astrophysics Data System (ADS)

Hosseinpoor, H. R.; Samadzadegan, F.; Dadras Javan, F.

2015-12-01

There are an increasingly large number of uses for Unmanned Aerial Vehicles (UAVs) from surveillance, mapping and target geolocation. However, most of commercial UAVs are equipped with low-cost navigation sensors such as C/A code GPS and a low-cost IMU on board, allowing a positioning accuracy of 5 to 10 meters. This low accuracy which implicates that it cannot be used in applications that require high precision data on cm-level. This paper presents a precise process for geolocation of ground targets based on thermal video imagery acquired by small UAV equipped with RTK GPS. The geolocation data is filtered using a linear Kalman filter, which provides a smoothed estimate of target location and target velocity. The accurate geo-locating of targets during image acquisition is conducted via traditional photogrammetric bundle adjustment equations using accurate exterior parameters achieved by on board IMU and RTK GPS sensors and Kalman filtering and interior orientation parameters of thermal camera from pre-flight laboratory calibration process.

Feasibility of Using Synthetic Aperture Radar to Aid UAV Navigation

PubMed Central

Nitti, Davide O.; Bovenga, Fabio; Chiaradia, Maria T.; Greco, Mario; Pinelli, Gianpaolo

2015-01-01

This study explores the potential of Synthetic Aperture Radar (SAR) to aid Unmanned Aerial Vehicle (UAV) navigation when Inertial Navigation System (INS) measurements are not accurate enough to eliminate drifts from a planned trajectory. This problem can affect medium-altitude long-endurance (MALE) UAV class, which permits heavy and wide payloads (as required by SAR) and flights for thousands of kilometres accumulating large drifts. The basic idea is to infer position and attitude of an aerial platform by inspecting both amplitude and phase of SAR images acquired onboard. For the amplitude-based approach, the system navigation corrections are obtained by matching the actual coordinates of ground landmarks with those automatically extracted from the SAR image. When the use of SAR amplitude is unfeasible, the phase content can be exploited through SAR interferometry by using a reference Digital Terrain Model (DTM). A feasibility analysis was carried out to derive system requirements by exploring both radiometric and geometric parameters of the acquisition setting. We showed that MALE UAV, specific commercial navigation sensors and SAR systems, typical landmark position accuracy and classes, and available DTMs lead to estimate UAV coordinates with errors bounded within ±12 m, thus making feasible the proposed SAR-based backup system. PMID:26225977

Feasibility of Using Synthetic Aperture Radar to Aid UAV Navigation.

PubMed

Nitti, Davide O; Bovenga, Fabio; Chiaradia, Maria T; Greco, Mario; Pinelli, Gianpaolo

2015-07-28

This study explores the potential of Synthetic Aperture Radar (SAR) to aid Unmanned Aerial Vehicle (UAV) navigation when Inertial Navigation System (INS) measurements are not accurate enough to eliminate drifts from a planned trajectory. This problem can affect medium-altitude long-endurance (MALE) UAV class, which permits heavy and wide payloads (as required by SAR) and flights for thousands of kilometres accumulating large drifts. The basic idea is to infer position and attitude of an aerial platform by inspecting both amplitude and phase of SAR images acquired onboard. For the amplitude-based approach, the system navigation corrections are obtained by matching the actual coordinates of ground landmarks with those automatically extracted from the SAR image. When the use of SAR amplitude is unfeasible, the phase content can be exploited through SAR interferometry by using a reference Digital Terrain Model (DTM). A feasibility analysis was carried out to derive system requirements by exploring both radiometric and geometric parameters of the acquisition setting. We showed that MALE UAV, specific commercial navigation sensors and SAR systems, typical landmark position accuracy and classes, and available DTMs lead to estimated UAV coordinates with errors bounded within ±12 m, thus making feasible the proposed SAR-based backup system.

Systemic Approach to Elevation Data Acquisition for Geophysical Survey Alignments in Hilly Terrains Using UAVs

NASA Astrophysics Data System (ADS)

Ismail, M. A. M.; Kumar, N. S.; Abidin, M. H. Z.; Madun, A.

2018-04-01

This study is about systematic approach to photogrammetric survey that is applicable in the extraction of elevation data for geophysical surveys in hilly terrains using Unmanned Aerial Vehicles (UAVs). The outcome will be to acquire high-quality geophysical data from areas where elevations vary by locating the best survey lines. The study area is located at the proposed construction site for the development of a water reservoir and related infrastructure in Kampus Pauh Putra, Universiti Malaysia Perlis. Seismic refraction surveys were carried out for the modelling of the subsurface for detailed site investigations. Study were carried out to identify the accuracy of the digital elevation model (DEM) produced from an UAV. At 100 m altitude (flying height), over 135 overlapping images were acquired using a DJI Phantom 3 quadcopter. All acquired images were processed for automatic 3D photo-reconstruction using Agisoft PhotoScan digital photogrammetric software, which was applied to all photogrammetric stages. The products generated included a 3D model, dense point cloud, mesh surface, digital orthophoto, and DEM. In validating the accuracy of the produced DEM, the coordinates of the selected ground control point (GCP) of the survey line in the imaging area were extracted from the generated DEM with the aid of Global Mapper software. These coordinates were compared with the GCPs obtained using a real-time kinematic global positioning system. The maximum percentage of difference between GCP’s and photogrammetry survey is 13.3 %. UAVs are suitable for acquiring elevation data for geophysical surveys which can save time and cost.

Field determination of multipollutant, open area combustion source emission factors with a hexacopter unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Aurell, J.; Mitchell, W.; Chirayath, V.; Jonsson, J.; Tabor, D.; Gullett, B.

2017-10-01

An emission sensor/sampler system was coupled to a National Aeronautics and Space Administration (NASA) hexacopter unmanned aerial vehicle (UAV) to characterize gases and particles in the plumes emitted from open burning of military ordnance. The UAV/sampler was tested at two field sites with test and sampling flights spanning over 16 h of flight time. The battery-operated UAV was remotely maneuvered into the plumes at distances from the pilot of over 600 m and at altitudes of up to 122 m above ground level. While the flight duration could be affected by sampler payload (3.2-4.6 kg) and meteorological conditions, the 57 sampling flights, ranging from 4 to 12 min, were typically terminated when the plume concentrations of CO2 were diluted to near ambient levels. Two sensor/sampler systems, termed ;Kolibri,; were variously configured to measure particulate matter, metals, chloride, perchlorate, volatile organic compounds, chlorinated dioxins/furans, and nitrogen-based organics for determination of emission factors. Gas sensors were selected based on their applicable concentration range, light weight, freedom from interferents, and response/recovery times. Samplers were designed, constructed, and operated based on U.S. Environmental Protection Agency (EPA) methods and quality control criteria. Results show agreement with published emission factors and good reproducibility (e.g., 26% relative standard deviation for PM2.5). The UAV/Kolibri represents a significant advance in multipollutant emission characterization capabilities for open area sources, safely and effectively making measurements heretofore deemed too hazardous for personnel or beyond the reach of land-based samplers.

Georeferencing UAS Derivatives Through Point Cloud Registration with Archived Lidar Datasets

NASA Astrophysics Data System (ADS)

Magtalas, M. S. L. Y.; Aves, J. C. L.; Blanco, A. C.

2016-10-01

Georeferencing gathered images is a common step before performing spatial analysis and other processes on acquired datasets using unmanned aerial systems (UAS). Methods of applying spatial information to aerial images or their derivatives is through onboard GPS (Global Positioning Systems) geotagging, or through tying of models through GCPs (Ground Control Points) acquired in the field. Currently, UAS (Unmanned Aerial System) derivatives are limited to meter-levels of accuracy when their generation is unaided with points of known position on the ground. The use of ground control points established using survey-grade GPS or GNSS receivers can greatly reduce model errors to centimeter levels. However, this comes with additional costs not only with instrument acquisition and survey operations, but also in actual time spent in the field. This study uses a workflow for cloud-based post-processing of UAS data in combination with already existing LiDAR data. The georeferencing of the UAV point cloud is executed using the Iterative Closest Point algorithm (ICP). It is applied through the open-source CloudCompare software (Girardeau-Montaut, 2006) on a `skeleton point cloud'. This skeleton point cloud consists of manually extracted features consistent on both LiDAR and UAV data. For this cloud, roads and buildings with minimal deviations given their differing dates of acquisition are considered consistent. Transformation parameters are computed for the skeleton cloud which could then be applied to the whole UAS dataset. In addition, a separate cloud consisting of non-vegetation features automatically derived using CANUPO classification algorithm (Brodu and Lague, 2012) was used to generate a separate set of parameters. Ground survey is done to validate the transformed cloud. An RMSE value of around 16 centimeters was found when comparing validation data to the models georeferenced using the CANUPO cloud and the manual skeleton cloud. Cloud-to-cloud distance computations of CANUPO and manual skeleton clouds were obtained with values for both equal to around 0.67 meters at 1.73 standard deviation.

Fiber Optic Wing Shape Sensing on NASA's Ikhana UAV

NASA Technical Reports Server (NTRS)

Richards, Lance; Parker, Allen R.; Ko, William L.; Piazza, Anthony

2008-01-01

Fiber Optic Wing Shape Sensing on Ikhana involves five major areas 1) Algorithm development: Local-strain-to-displacement algorithms have been developed for complex wing shapes for real-time implementation (NASA TP-2007-214612, patent application submitted) 2) FBG system development: Dryden advancements to fiber optic sensing technology have increased data sampling rates to levels suitable for monitoring structures in flight (patent application submitted) 3) Instrumentation: 2880 FBG strain sensors have been successfully installed on the Ikhana wings 4) Ground Testing: Fiber optic wing shape sensing methods for high aspect ratio UAVs have been validated through extensive ground testing in Dryden s Flight Loads Laboratory 5) Flight Testing: Real time fiber Bragg strain measurements successfully acquired and validated in flight (4/28/2008) Real-time fiber optic wing shape sensing successfully demonstrated in flight

UAV Control on the Basis of 3D Landmark Bearing-Only Observations

PubMed Central

Karpenko, Simon; Konovalenko, Ivan; Miller, Alexander; Miller, Boris; Nikolaev, Dmitry

2015-01-01

The article presents an approach to the control of a UAV on the basis of 3D landmark observations. The novelty of the work is the usage of the 3D RANSAC algorithm developed on the basis of the landmarks’ position prediction with the aid of a modified Kalman-type filter. Modification of the filter based on the pseudo-measurements approach permits obtaining unbiased UAV position estimation with quadratic error characteristics. Modeling of UAV flight on the basis of the suggested algorithm shows good performance, even under significant external perturbations. PMID:26633394

3D landslide motion from a UAV-derived time-series of morphological attributes

NASA Astrophysics Data System (ADS)

Valasia Peppa, Maria; Mills, Jon Philip; Moore, Philip; Miller, Pauline; Chambers, Jon

2017-04-01

Landslides are recognised as dynamic and significantly hazardous phenomena. Time-series observations can improve the understanding of a landslide's complex behaviour and aid assessment of its geometry and kinematics. Conventional quantification of landslide motion involves the installation of survey markers into the ground at discrete locations and periodic observations over time. However, such surveying is labour intensive, provides limited spatial resolution, is occasionally hazardous for steep terrain, or even impossible for inaccessible mountainous areas. The emergence of mini unmanned aerial vehicles (UAVs) equipped with off-the-shelf compact cameras, alongside the structure-from-motion (SfM) photogrammetric pipeline and modern pixel-based matching approaches, has expedited the automatic generation of high resolution digital elevation models (DEMs). Moreover, cross-correlation functions applied to finely co-registered consecutive orthomosaics and/or DEMs have been widely used to determine the displacement of moving features in an automated way, resulting in high spatial resolution motion vectors. This research focuses on estimating the 3D displacement field of an active slow moving earth-slide earth-flow landslide located in Lias mudrocks of North Yorkshire, UK, with the ultimate aim of assessing landslide deformation patterns. The landslide extends approximately 290 m E-W and 230 m N-S, with an average slope of 12˚ and 50 m elevation difference from N-S. Cross-correlation functions were applied to an eighteen-month duration, UAV-derived, time-series of morphological attributes in order to determine motion vectors for subsequent landslide analysis. A self-calibrating bundle adjustment was firstly incorporated into the SfM pipeline and utilised to process imagery acquired using a Panasonic Lumix DMC-LX5 compact camera from a mini fixed-wing Quest 300 UAV, with 2 m wingspan and maximum 5 kg payload. Data from six field campaigns were used to generate a DEM time-series at 6 cm spatial resolution. DEMs were georeferenced into a common reference frame using control information from surveyed ground control points. The accuracy of the co-registration was estimated from planimetric and vertical RMS errors at independent checkpoints as 4 cm and 3 cm respectively. Afterwards, various morphological attributes, including shaded relief, curvature and openness were calculated from the UAV-derived DEMs. These attributes are indicative of the local structures of discernible geomorphological features (e.g. scarps, ridges, cracks, etc.), the motion of which can be monitored using the cross-correlation algorithm. Multiple experiments were conducted to test the performance of the cross-correlation function implemented on successive epochs. Two benchmark datasets were used for validation of the cross-correlation results: a) the motion vectors generated from the surveyed 3D position of installed markers; b) the calculated displacements of features, manually tracked from successive UAV-derived orthomosaics. Both benchmark datasets detected a maximum planimetric displacement of approximately 1 m at the foot of the landslide, with a dominant N-S orientation, between December 2014 and May 2016. Preliminary cross-correlation results illustrated a similar planimetric motion in both magnitude and orientation, however user intervention was required to filter spurious displacement vectors.

Comparison of Unmanned Aerial Vehicle Technology Versus Standard Practice in Identification of Hazards at a Mass Casualty Incident Scenario by Primary Care Paramedic Students.

PubMed

Jain, Trevor; Sibley, Aaron; Stryhn, Henrik; Hubloue, Ives

2018-01-31

Introduction The proliferation of unmanned aerial vehicles (UAV) has the potential to change the situational awareness of incident commanders allowing greater scene safety. The aim of this study was to compare UAV technology to standard practice (SP) in hazard identification during a simulated multi-vehicle motor collision (MVC) in terms of time to identification, accuracy and the order of hazard identification. A prospective observational cohort study was conducted with 21 students randomized into UAV or SP group, based on a MVC with 7 hazards. The UAV group remained at the UAV ground station while the SP group approached the scene. After identifying hazards the time and order was recorded. The mean time (SD, range) to identify the hazards were 3 minutes 41 seconds (1 minute 37 seconds, 1 minute 48 seconds-6 minutes 51 seconds) and 2 minutes 43 seconds (55 seconds, 1 minute 43 seconds-4 minutes 38 seconds) in UAV and SP groups corresponding to a mean difference of 58 seconds (P=0.11). A non-parametric permutation test showed a significant (P=0.04) difference in identification order. Both groups had 100% accuracy in hazard identification with no statistical difference in time for hazard identification. A difference was found in the identification order of hazards. (Disaster Med Public Health Preparedness. 2018;page 1 of 4).

Autonomous unmanned air vehicles (UAV) techniques

NASA Astrophysics Data System (ADS)

Hsu, Ming-Kai; Lee, Ting N.

2007-04-01

The UAVs (Unmanned Air Vehicles) have great potentials in different civilian applications, such as oil pipeline surveillance, precision farming, forest fire fighting (yearly), search and rescue, boarder patrol, etc. The related industries of UAVs can create billions of dollars for each year. However, the road block of adopting UAVs is that it is against FAA (Federal Aviation Administration) and ATC (Air Traffic Control) regulations. In this paper, we have reviewed the latest technologies and researches on UAV navigation and obstacle avoidance. We have purposed a system design of Jittering Mosaic Image Processing (JMIP) with stereo vision and optical flow to fulfill the functionalities of autonomous UAVs.

Visual navigation of the UAVs on the basis of 3D natural landmarks

NASA Astrophysics Data System (ADS)

Karpenko, Simon; Konovalenko, Ivan; Miller, Alexander; Miller, Boris; Nikolaev, Dmitry

2015-12-01

This work considers the tracking of the UAV (unmanned aviation vehicle) on the basis of onboard observations of natural landmarks including azimuth and elevation angles. It is assumed that UAV's cameras are able to capture the angular position of reference points and to measure the angles of the sight line. Such measurements involve the real position of UAV in implicit form, and therefore some of nonlinear filters such as Extended Kalman filter (EKF) or others must be used in order to implement these measurements for UAV control. Recently it was shown that modified pseudomeasurement method may be used to control UAV on the basis of the observation of reference points assigned along the UAV path in advance. However, the use of such set of points needs the cumbersome recognition procedure with the huge volume of on-board memory. The natural landmarks serving as such reference points which may be determined on-line can significantly reduce the on-board memory and the computational difficulties. The principal difference of this work is the usage of the 3D reference points coordinates which permits to determine the position of the UAV more precisely and thereby to guide along the path with higher accuracy which is extremely important for successful performance of the autonomous missions. The article suggests the new RANSAC for ISOMETRY algorithm and the use of recently developed estimation and control algorithms for tracking of given reference path under external perturbation and noised angular measurements.

Monitoring landslide dynamics using timeseries of UAV imagery

NASA Astrophysics Data System (ADS)

de Jong, S. M.; Van Beek, L. P.

2017-12-01

Landslides are worldwide occurring processes that can have large economic impact and sometimes result in fatalities. Multiple factors are important in landslide processes and can make an area prone to landslide activity. Human factors like drainage and removal of vegetation or land clearing are examples of factors that may cause a landslide. Other environmental factors such as topography and the shear strength of the slope material are more difficult to control. Triggering factors for landslides are typically heavy rainfall events or sometimes by earthquakes or under cutting processes by a river. The collection of data about existing landslides in a given area is important for predicting future landslides in that region. We have setup a monitoring program for landslide using cameras aboard Unmanned Airborne Vehicles. UAV with cameras are able to collect ultra-high resolution images and UAVs can be operated in a very flexible way, they just fit in the back of a car. Here, in this study we used Unmanned Aerial Vehicles to collect a time series of high-resolution images over landslides in France and Australia. The algorithm used to process the UAV images into OrthoMosaics and OrthoDEMs is Structure from Motion (SfM). The process generally results in centimeter precision in the horizontal and vertical direction. Such multi-temporal datasets enable the detection of landslide area, the leading edge slope, temporal patterns and volumetric changes of particular areas of the landslide. We measured and computed surface movement of the landslide using the COSI-Corr image correlation algorithm with ground validation. Our study shows the possibilities of generating accurate Digital Surface Models (DSMs) of landslides using images collected with an Unmanned Aerial Vehicle (UAV). The technique is robust and repeatable such that a substantial time series of datasets can be routinely collected. It is shown that a time-series of UAV images can be used to map landslide movements with centimeter accuracy. It also found that there can be a cyclical nature to the slope of the leading edge of the landslide, suggesting that the steepness of the slope can be used to predict the next forward surge of the leading edge.

Automated geographic registration and radiometric correction for UAV-based mosaics

NASA Astrophysics Data System (ADS)

Thomasson, J. Alex; Shi, Yeyin; Sima, Chao; Yang, Chenghai; Cope, Dale A.

2017-05-01

Texas A and M University has been operating a large-scale, UAV-based, agricultural remote-sensing research project since 2015. To use UAV-based images in agricultural production, many high-resolution images must be mosaicked together to create an image of an agricultural field. Two key difficulties to science-based utilization of such mosaics are geographic registration and radiometric calibration. In our current research project, image files are taken to the computer laboratory after the flight, and semi-manual pre-processing is implemented on the raw image data, including ortho-mosaicking and radiometric calibration. Ground control points (GCPs) are critical for high-quality geographic registration of images during mosaicking. Applications requiring accurate reflectance data also require radiometric-calibration references so that reflectance values of image objects can be calculated. We have developed a method for automated geographic registration and radiometric correction with targets that are installed semi-permanently at distributed locations around fields. The targets are a combination of black (≍5% reflectance), dark gray (≍20% reflectance), and light gray (≍40% reflectance) sections that provide for a transformation of pixel-value to reflectance in the dynamic range of crop fields. The exact spectral reflectance of each target is known, having been measured with a spectrophotometer. At the time of installation, each target is measured for position with a real-time kinematic GPS receiver to give its precise latitude and longitude. Automated location of the reference targets in the images is required for precise, automated, geographic registration; and automated calculation of the digital-number to reflectance transformation is required for automated radiometric calibration. To validate the system for radiometric calibration, a calibrated UAV-based image mosaic of a field was compared to a calibrated single image from a manned aircraft. Reflectance values in selected zones of each image were strongly linearly related, and the average error of UAV-mosaic reflectances was 3.4% in the red band, 1.9% in the green band, and 1.5% in the blue band. Based on these results, the proposed physical system and automated software for calibrating UAV mosaics show excellent promise.

In-Flight Technique for Acquiring Mid- And Far-Field Sonic Boom Signatures

NASA Technical Reports Server (NTRS)

Stansbery, Eugene G.; Baize, Daniel G.; Maglieri, Domenic, J.

1999-01-01

Flight test experiments have been conducted to establish the feasibility of obtaining sonic boom signature measurements below a supersonic aircraft using the NASA Portable Automatic Triggering System (PATS) mounted in the USMC Pioneer Unmanned Aerial Vehicle (UAV). This study forms a part of the NASA sonic boom minimization activities, specifically the demonstration of persistence of modified boom signatures to very large distances in a real atmosphere. The basic objective of the measurement effort was to obtain a qualitative view of the sonic boom signature in terms of its shape, number of shocks, their locations, and their relative strength. Results suggest that the technique may very well provide quantitative information relative to mid-field and far-field boom signatures. The purpose of this presentation is to describe the arrangement and operation of this in-flight system and to present the resulting sonic boom measurements. Adaption and modification of two PATS to the UAV payload section are described and include transducer location, mounting arrangement and recording system isolation. Ground static runup, takeoff and landing, and cruise flight checkouts regarding UAV propeller and flow noise on the PATS automated triggering system and recording mode are discussed. For the proof-of-concept tests, the PATS instrumented UAV was flown under radar control in steady-level flight at the altitude of 8700 feet MSL and at a cruise speed of about 60 knots. The USN F-4N sonic boom generating aircraft was vectored over the UAV on reciprocal headings at altitudes of about 1 1,000 feet MSL and 13,000 feet MSL at about Mach 1. 15. Sonic boom signatures were acquired on both PATS for all six supersonic passes. Although the UAV propeller noise is clearly evident in all the measurements, the F-4 boom signature is clearly distinguishable and is typically N-wave in character with sharply rising shock fronts and with a mid-shock associated with the inlet-wing juncture. Consideration is being given to adapting the PATS/TJAV measurements technique to the NASA Learjet to determine feasibility of acquiring in-flight boom signatures in the altitude range of 10,000 feet to 40,000 feet.

UAV measurements of aerosol properties at the Cyprus institute

NASA Astrophysics Data System (ADS)

Neitola, Kimmo; Sciare, Jean; Keleshis, Christos; Pikridas, Michael; Argyrides, Marios; Vouterakos, Panagiotis; Antoniou, Panyiota; Apostolou, Apostolos; Savvides, Constantinos; Vrekoussis, Mihalis; Mihalopoulos, Nikos; Biskos, George; Gao, Ru-Shan; Murphy, Daniel; Schrod, Jann; Weber, Daniel; Bingemer, Heinz; Mocnik, Grisa

2017-04-01

Unmanned Aerial Vehicles (UAVs) provide a cost-effective and easy-to-use method to document the vertical profiles of aerosol particles and their physical and optical properties, within and above the boundary layer. These observations combined with satellite and ground data together can provide important information and model constrains regarding the impact of aerosols on the air quality and regional climate. Cyprus is a unique place to observe long-range transported pollution and dust originating from different areas (Europe, Africa, Turkey, and Middle East) and perform such aerosol profiling. The USRL team at the Cyprus Institute has recently started weekly routine flights with a newly developed UAV fleet to build a unique dataset of vertical profile observations. Instrumentation on the UAVs includes miniature Scanning Aerosol Sun Photometer (miniSASP, Murphy et al., 2015), Printed Optical Particle Spectrometer (POPS, Gao et al., 2016), Ice nuclei sampler (IN) and Dual Wavelength absorption Prototype (DWP) together with the measured meteorological parameters (P, T and RH). The UAV fleet is still expanding, as well as the instrumentation, and preliminary test flights have led to very promising results. The UAV ascend up to approximately the middle of the boundary layer, defined by LIDAR measurements at Limassol, where the UAV will fly on one altitude for several minutes ensuring stable data collection. After flying on one altitude, the UAV will continue ascending above the boundary layer, where another level flight will take place for data gathering, before descending for safe landing. The miniSASP measures the sun irradiance and sky radiance at four wavelengths (460, 550, 670 and 680nm) by doing continuous almucantar scans every 30 s. The instrument installation compensates for the pitch and roll of the UAV with 4 Hz frequency. For this reason, the flights are designed to maintain level flight conditions, to ensure proper data acquisition, and to obtain data from discrete altitudes and not only during the ascend and descend periods. The POPS measures the particle size distribution in the range of 140-3000 nm diameter within 14 size channels. The POPS was successfully compared to another OPC (MetOne, model 212 profiler) on separate flights during the same day with coinciding results. The routine flights will continue for a year, once or twice a week, targeting different air mass origins and synoptic conditions. The aim is to build a comprehensive dataset by merging atmospheric data measured both by UAVs and ground-based in situ observations obtained 1) at the Agia Marina Xyliatou remote station (500m asl) and 2) at the free troposphere Troodos altitude station (1800m asl). This project received funding from the European Union's Seventh Framework Programme (FP7) project BACCHUS under grant agreement no. 603445 and from the European Union's Horizon 2020 research and innovation programme ACTRIS-2 under grant agreement No 654109.

Corn and sorghum phenotyping using a fixed-wing UAV-based remote sensing system

NASA Astrophysics Data System (ADS)

Shi, Yeyin; Murray, Seth C.; Rooney, William L.; Valasek, John; Olsenholler, Jeff; Pugh, N. Ace; Henrickson, James; Bowden, Ezekiel; Zhang, Dongyan; Thomasson, J. Alex

2016-05-01

Recent development of unmanned aerial systems has created opportunities in automation of field-based high-throughput phenotyping by lowering flight operational cost and complexity and allowing flexible re-visit time and higher image resolution than satellite or manned airborne remote sensing. In this study, flights were conducted over corn and sorghum breeding trials in College Station, Texas, with a fixed-wing unmanned aerial vehicle (UAV) carrying two multispectral cameras and a high-resolution digital camera. The objectives were to establish the workflow and investigate the ability of UAV-based remote sensing for automating data collection of plant traits to develop genetic and physiological models. Most important among these traits were plant height and number of plants which are currently manually collected with high labor costs. Vegetation indices were calculated for each breeding cultivar from mosaicked and radiometrically calibrated multi-band imagery in order to be correlated with ground-measured plant heights, populations and yield across high genetic-diversity breeding cultivars. Growth curves were profiled with the aerial measured time-series height and vegetation index data. The next step of this study will be to investigate the correlations between aerial measurements and ground truth measured manually in field and from lab tests.

Time-Critical Cooperative Path Following of Multiple UAVs: Case Studies

DTIC Science & Technology

2012-10-30

control algorithm for UAVs in 3D space. Section IV derives a strategy for time-critical cooperative path following of multiple UAVs that relies on the...UAVs in 3D space, in which a fleet of UAVs is tasked to converge to and follow a set of desired feasible paths so as to meet spatial and temporal...cooperative trajectory generation is not addressed in this paper. In fact, it is assumed that a set of desired 3D time trajectories pd,i(td) : R → R3

Mathematical model of unmanned aerial vehicle used for endurance autonomous monitoring

NASA Astrophysics Data System (ADS)

Chelaru, Teodor-Viorel; Chelaru, Adrian

2014-12-01

The paper purpose is to present some aspects regarding the control system of unmanned aerial vehicle - UAV, used to local observations, surveillance and monitoring interest area. The calculus methodology allows a numerical simulation of UAV evolution in bad atmospheric conditions by using nonlinear model, as well as a linear one for obtaining guidance command. The UAV model which will be presented has six DOF (degrees of freedom), and autonomous control system. This theoretical development allows us to build stability matrix, command matrix and control matrix and finally to analyse the stability of autonomous UAV flight. A robust guidance system, based on uncoupled state will be evaluated for different fly conditions and the results will be presented. The flight parameters and guidance will be analysed.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chelaru, Teodor-Viorel, E-mail: teodor.chelaru@upb.ro; Chelaru, Adrian, E-mail: achelaru@incas.ro

The paper purpose is to present some aspects regarding the control system of unmanned aerial vehicle - UAV, used to local observations, surveillance and monitoring interest area. The calculus methodology allows a numerical simulation of UAV evolution in bad atmospheric conditions by using nonlinear model, as well as a linear one for obtaining guidance command. The UAV model which will be presented has six DOF (degrees of freedom), and autonomous control system. This theoretical development allows us to build stability matrix, command matrix and control matrix and finally to analyse the stability of autonomous UAV flight. A robust guidance system,more » based on uncoupled state will be evaluated for different fly conditions and the results will be presented. The flight parameters and guidance will be analysed.« less

Terrain mapping and control of unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Kang, Yeonsik

In this thesis, methods for terrain mapping and control of unmanned aerial vehicles (UAVs) are proposed. First, robust obstacle detection and tracking algorithm are introduced to eliminate the clutter noise uncorrelated with the real obstacle. This is an important problem since most types of sensor measurements are vulnerable to noise. In order to eliminate such noise, a Kalman filter-based interacting multiple model (IMM) algorithm is employed to effectively detect obstacles and estimate their positions precisely. Using the outcome of the IMM-based obstacle detection algorithm, a new method of building a probabilistic occupancy grid map is proposed based on Bayes rule in probability theory. Since the proposed map update law uses the outputs of the IMM-based obstacle detection algorithm, simultaneous tracking of moving targets and mapping of stationary obstacles are possible. This can be helpful especially in a noisy outdoor environment where different types of obstacles exist. Another feature of the algorithm is its capability to eliminate clutter noise as well as measurement noise. The proposed algorithm is simulated in Matlab using realistic sensor models. The results show close agreement with the layout of real obstacles. An efficient method called "quadtree" is used to process massive geographical information in a convenient manner. The algorithm is evaluated in a realistic simulation environment called RIPTIDE, which the NASA Ames Research Center developed to access the performance of complicated software for UAVs. Supposing that a UAV is equipped with abovementioned obstacle detection and mapping algorithm, the control problem of a small fixed-wing UAV is studied. A Nonlinear Model Predictive Control (NMPC is designed as a high level controller for the fixed-wing UAV using a kinematic model of the UAV. The kinematic model is employed because of the assumption that there exist low level controls on the UAV. The UAV dynamics are nonlinear with input constraints which is the main challenge explored in this thesis. The control objective of the NMPC is determined to track a desired line, and the analysis of the designed NMPC's stability is followed to find the conditions that can assure stability. Then, the control objective is extended to track adjoined multiple line segments with obstacle avoidance capability. In simulation, the performance of the NMPC is superb with fast convergence and small overshoot. The computation time is not a burden for a fixed-wing UAV controller with a Pentium level on-board computer that provides a reasonable control update rate.

Forest structure analysis combining laser scanning with digital airborne photogrammetry

NASA Astrophysics Data System (ADS)

Lissak, Candide; Onda, Yuichi; Kato, Hiroaki

2017-04-01

The interest of Light Detection and Ranging (LiDAR) for vegetation structure analysis has been demonstrated in several research context. Indeed, airborne or ground Lidar surveys can provide detailed three-dimensional data of the forest structure from understorey forest to the canopy. To characterize at different timescale the vegetation components in dense cedar forests we can combine several sources point clouds from Lidar survey and photogrammetry data. For our study, Terrestrial Laser Scanning (TLS-Leica ScanStation C10 processed with Cyclone software) have been lead in three forest areas (≈ 200m2 each zone) mainly composed of japanese cedar (Japonica cryptomeria), in the region of Fukushima (Japan). The study areas are characterized by various vegetation densities. For the 3 areas, Terrestrial laser scanning has been performed from several location points and several heights. Various floors shootings (ground, 4m, 6m and 18m high) were able with the use of a several meters high tower implanted to study the canopy evolution following the Fukushima Daiishi nuclear power plant accident. The combination of all scanners provides a very dense 3D point cloud of ground and canopy structure (average 300 000 000 points). For the Tochigi forest area, a first test of a low-cost Unmanned Aerial Vehicle (UAV) photogrammetry has been lead and calibrated by ground GPS measurements to determine the coordinates of points. TLS combined to UAV photogrammetry make it possible to obtain information on vertical and horizontal structure of the Tochigi forest. This combination of technologies will allow the forest structure mapping, morphometry analysis and the assessment of biomass volume evolution from multi-temporal point clouds. In our research, we used a low-cost UAV 3 Advanced (200 m2 cover, 1300 pictures...). Data processing were performed using PotoScan Pro software to obtain a very dense point clouds to combine to TLS data set. This low-cost UAV photogrammetry data has been successfully used to derive information on the canopy cover. The purpose of this poster is to present the usability of combined remote sensing methods for forest structure analysis and 3D model reconstitution for a trend analysis of the forest changes.

Improving Rangeland Monitoring and Assessment: Integrating Remote Sensing, GIS, and Unmanned Aerial Vehicle Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Robert Paul Breckenridge

2007-05-01

Creeping environmental changes are impacting some of the largest remaining intact parcels of sagebrush steppe ecosystems in the western United States, creating major problems for land managers. The Idaho National Laboratory (INL), located in southeastern Idaho, is part of the sagebrush steppe ecosystem, one of the largest ecosystems on the continent. Scientists at the INL and the University of Idaho have integrated existing field and remotely sensed data with geographic information systems technology to analyze how recent fires on the INL have influenced the current distribution of terrestrial vegetation. Three vegetation mapping and classification systems were used to evaluate themore » changes in vegetation caused by fires between 1994 and 2003. Approximately 24% of the sagebrush steppe community on the INL was altered by fire, mostly over a 5-year period. There were notable differences between methods, especially for juniper woodland and grasslands. The Anderson system (Anderson et al. 1996) was superior for representing the landscape because it includes playa/bare ground/disturbed area and sagebrush steppe on lava as vegetation categories. This study found that assessing existing data sets is useful for quantifying fire impacts and should be helpful in future fire and land use planning. The evaluation identified that data from remote sensing technologies is not currently of sufficient quality to assess the percentage of cover. To fill this need, an approach was designed using both helicopter and fixed wing unmanned aerial vehicles (UAVs) and image processing software to evaluate six cover types on field plots located on the INL. The helicopter UAV provided the best system compared against field sampling, but is more dangerous and has spatial coverage limitations. It was reasonably accurate for dead shrubs and was very good in assessing percentage of bare ground, litter and grasses; accuracy for litter and shrubs is questionable. The fixed wing system proved to be feasible and can collect imagery for very large areas in a short period of time. It was accurate for bare ground and grasses. Both UAV systems have limitations, but these will be reduced as the technology advances. In both cases, the UAV systems collected data at a much faster rate than possible on the ground. The study concluded that improvements in automating the image processing efforts would greatly improve use of the technology. In the near future, UAV technology may revolutionize rangeland monitoring in the same way Global Positioning Systems have affected navigation while conducting field activities.« less

Fixedwing UAV soundings of the boundary layer during the ScaleX 2015 summer campaign in southern Germany

NASA Astrophysics Data System (ADS)

Philipp, Andreas; Groos, Alexander; Petersen, Erik; Bischoff, Julian; Szogs, Sebastian; Beck, Christoph; Hähner, Jörg; Jacobeit, Jucundus

2016-04-01

In order to examine the potential to close the local water cycle budget and to evaluate models on different scales (among other aims) a fleet of 6 fixed wing UAVs has been operated by the Institute for Geography and the Institute for Informatics of the University of Augsburg during the ScaleX measurement campaign of the KIT/IMK-IFU (Karlsruher Institut für Technologie/Institut für Meteorologie und Klimatologie, Garmisch Partenkirchen). The site is located in southern Germany in a rural, hilly landscape at a small catchment tributing to the Ammersee and equipped with several ground based and remote sensing hydrological instruments. In order to complement these instruments by in situ measurements of the boundary layer, three intensive observation periods (IOPs) for taking temperature and humidity profiles took place, each with a different set up in order to evaluate optimal operation modes. The UAVs are all operated by the open hardware Apogee autopilot and sensor controller developed by ENAC (Ecole Nationale de l'Aviation Civile, Toulouse) operated by the PPRZ open source software package. The first IOP (30.06.-01.07.2015) was an experiment to cover a small site of 500 by 500 meters (well-apointed with hydrological instruments) in a 24 hours period as dense as possible. Thus three simultaneous helical profile flights (radius 70 m) have been run at each full hour around three different centres with heights ranging up to 1000 m above ground level (with special permissions). During a second IOP (15.07.2015) it has been tried to increase the frequence of profile flights up to 2 flights per hours between 7:30 and 14:00 CEST. These soundings have been accompanied by flyovers of a manned ultra light aircraft of the IMK-IFU. Finally a third experiment (06.08.2015) tried to evaluate longer flights (up to 55 minutes) of two UAVs at constant levels of 300 and 500 m above ground level between 6:00 and 14:00 CEST in order to cover the early diurnal cycle even more constantly by the in situ measurements. A midnight profile for measuring the staring conditions of the development has been measured up to a hight of 1600 m, which was the permitted limit for this campaign. Data analysis using a newly developed 3D software showed that these flight experiments are able to reveal several distinct meteorological processes developing during the diurnal cycle which are shortly discussed on the poster.

4D very high-resolution topography monitoring of surface deformation using UAV-SfM framework.

NASA Astrophysics Data System (ADS)

Clapuyt, François; Vanacker, Veerle; Schlunegger, Fritz; Van Oost, Kristof

2016-04-01

During the last years, exploratory research has shown that UAV-based image acquisition is suitable for environmental remote sensing and monitoring. Image acquisition with cameras mounted on an UAV can be performed at very-high spatial resolution and high temporal frequency in the most dynamic environments. Combined with Structure-from-Motion algorithm, the UAV-SfM framework is capable of providing digital surface models (DSM) which are highly accurate when compared to other very-high resolution topographic datasets and highly reproducible for repeated measurements over the same study area. In this study, we aim at assessing (1) differential movement of the Earth's surface and (2) the sediment budget of a complex earthflow located in the Central Swiss Alps based on three topographic datasets acquired over a period of 2 years. For three time steps, we acquired aerial photographs with a standard reflex camera mounted on a low-cost and lightweight UAV. Image datasets were then processed with the Structure-from-Motion algorithm in order to reconstruct a 3D dense point cloud representing the topography. Georeferencing of outputs has been achieved based on the ground control point (GCP) extraction method, previously surveyed on the field with a RTK GPS. Finally, digital elevation model of differences (DOD) has been computed to assess the topographic changes between the three acquisition dates while surface displacements have been quantified by using image correlation techniques. Our results show that the digital elevation model of topographic differences is able to capture surface deformation at cm-scale resolution. The mean annual displacement of the earthflow is about 3.6 m while the forefront of the landslide has advanced by ca. 30 meters over a period of 18 months. The 4D analysis permits to identify the direction and velocity of Earth movement. Stable topographic ridges condition the direction of the flow with highest downslope movement on steep slopes, and diffuse movement due to lateral sediment flux in the central part of the earthflow.

UAV-LiDAR accuracy and comparison to Structure from Motion photogrammetry

NASA Astrophysics Data System (ADS)

Kucharczyk, M.; Hugenholtz, C.; Zou, X.; Nesbit, P. R.; Barchyn, T.

2016-12-01

We compare the spatial accuracy of a UAV-LiDAR system with Structure from Motion (SfM) photogrammetry. UAV-based LiDAR remote sensing potentially offers advantages over SfM photogrammetry in vegetated terrain, particularly with respect to canopy penetration and related measurements of ground surface elevation and vegetation height; however, little quantitative evidence has been presented to date. To address this, we performed a case study at a field site in Alberta, Canada with six different land cover types: short grass, tall grass, short shrubs, tall shrubs, deciduous trees, and coniferous trees. Both UAV datasets were acquired on the same day. The SfM dataset was derived from images acquired by a senseFly eBee fixed-wing UAV equipped with a 16.1 megapixel RGB camera. The UAV-LiDAR system is a proprietary design that consists of a single-rotor helicopter (2-m rotor diameter) equipped with a Riegl VUX-1UAV laser scanner, KVH 1750 inertial measurement unit, and dual NovAtel GNSS receivers. We measured vegetation height from at least 30 samples in each land cover type and acquired check point measurements to determine horizontal and vertical accuracy. Vegetation height was measured manually for grasses and shrubs with a level staff, and with a total station for trees. Coordinates of horizontal and vertical check points were surveyed with real-time kinematic (RTK) GNSS. We followed standard methods for computing horizontal and vertical accuracies based on the 2015 guidelines from the American Society of Photogrammetry and Remote Sensing. Results will be presented at the AGU Fall Meeting.

Vertical Accuracy Evaluation of Aster GDEM2 Over a Mountainous Area Based on Uav Photogrammetry

NASA Astrophysics Data System (ADS)

Liang, Y.; Qu, Y.; Guo, D.; Cui, T.

2018-05-01

Global digital elevation models (GDEM) provide elementary information on heights of the Earth's surface and objects on the ground. GDEMs have become an important data source for a range of applications. The vertical accuracy of a GDEM is critical for its applications. Nowadays UAVs has been widely used for large-scale surveying and mapping. Compared with traditional surveying techniques, UAV photogrammetry are more convenient and more cost-effective. UAV photogrammetry produces the DEM of the survey area with high accuracy and high spatial resolution. As a result, DEMs resulted from UAV photogrammetry can be used for a more detailed and accurate evaluation of the GDEM product. This study investigates the vertical accuracy (in terms of elevation accuracy and systematic errors) of the ASTER GDEM Version 2 dataset over a complex terrain based on UAV photogrammetry. Experimental results show that the elevation errors of ASTER GDEM2 are in normal distribution and the systematic error is quite small. The accuracy of the ASTER GDEM2 coincides well with that reported by the ASTER validation team. The accuracy in the research area is negatively correlated to both the slope of the terrain and the number of stereo observations. This study also evaluates the vertical accuracy of the up-sampled ASTER GDEM2. Experimental results show that the accuracy of the up-sampled ASTER GDEM2 data in the research area is not significantly reduced by the complexity of the terrain. The fine-grained accuracy evaluation of the ASTER GDEM2 is informative for the GDEM-supported UAV photogrammetric applications.

The control of a parallel hybrid-electric propulsion system for a small unmanned aerial vehicle using a CMAC neural network.

PubMed

Harmon, Frederick G; Frank, Andrew A; Joshi, Sanjay S

2005-01-01

A Simulink model, a propulsion energy optimization algorithm, and a CMAC controller were developed for a small parallel hybrid-electric unmanned aerial vehicle (UAV). The hybrid-electric UAV is intended for military, homeland security, and disaster-monitoring missions involving intelligence, surveillance, and reconnaissance (ISR). The Simulink model is a forward-facing simulation program used to test different control strategies. The flexible energy optimization algorithm for the propulsion system allows relative importance to be assigned between the use of gasoline, electricity, and recharging. A cerebellar model arithmetic computer (CMAC) neural network approximates the energy optimization results and is used to control the parallel hybrid-electric propulsion system. The hybrid-electric UAV with the CMAC controller uses 67.3% less energy than a two-stroke gasoline-powered UAV during a 1-h ISR mission and 37.8% less energy during a longer 3-h ISR mission.

Cooperative Search by UAV Teams: A Model Predictive Approach Using Dynamic Graphs

DTIC Science & Technology

2011-10-01

decentralized processing and control architecture. SLAMEM asset models accurately represent the Unicorn UAV platforms and other standard military platforms in...IMPLEMENTATION The CGBMPS algorithm has been successfully field-tested using both Unicorn [27] and Raven [20] UAV platforms. This section describes...the hardware-software system setup and implementation used for testing with Unicorns , Toyon’s UAV test platform. We also present some results from the

Using unmanned aerial vehicles and structure-from-motion photogrammetry to characterize sedimentary outcrops: An example from the Morrison Formation, Utah, USA

NASA Astrophysics Data System (ADS)

Chesley, J. T.; Leier, A. L.; White, S.; Torres, R.

2017-06-01

Recently developed data collection techniques allow for improved characterization of sedimentary outcrops. Here, we outline a workflow that utilizes unmanned aerial vehicles (UAV) and structure-from-motion (SfM) photogrammetry to produce sub-meter-scale outcrop reconstructions in 3-D. SfM photogrammetry uses multiple overlapping images and an image-based terrain extraction algorithm to reconstruct the location of individual points from the photographs in 3-D space. The results of this technique can be used to construct point clouds, orthomosaics, and digital surface models that can be imported into GIS and related software for further study. The accuracy of the reconstructed outcrops, with respect to an absolute framework, is improved with geotagged images or independently gathered ground control points, and the internal accuracy of 3-D reconstructions is sufficient for sub-meter scale measurements. We demonstrate this approach with a case study from central Utah, USA, where UAV-SfM data can help delineate complex features within Jurassic fluvial sandstones.

Development of a Rotary Wing Unmanned Aerial Vehicle (UAV) Simulation Model

DTIC Science & Technology

2014-03-01

Features Language URL Autopilot: DIY UAV - 2 DOF proportional controller - Kalman filtering C http://autopilot.sour ceforge.net Paperazzi - 3 DOF...proprtional controller - Basic navigation OCaml http://paparazzi.ena c.fr JSBSim - Basic control system blockset - Sample autopilot

UAV path planning using artificial potential field method updated by optimal control theory

NASA Astrophysics Data System (ADS)

Chen, Yong-bo; Luo, Guan-chen; Mei, Yue-song; Yu, Jian-qiao; Su, Xiao-long

2016-04-01

The unmanned aerial vehicle (UAV) path planning problem is an important assignment in the UAV mission planning. Based on the artificial potential field (APF) UAV path planning method, it is reconstructed into the constrained optimisation problem by introducing an additional control force. The constrained optimisation problem is translated into the unconstrained optimisation problem with the help of slack variables in this paper. The functional optimisation method is applied to reform this problem into an optimal control problem. The whole transformation process is deduced in detail, based on a discrete UAV dynamic model. Then, the path planning problem is solved with the help of the optimal control method. The path following process based on the six degrees of freedom simulation model of the quadrotor helicopters is introduced to verify the practicability of this method. Finally, the simulation results show that the improved method is more effective in planning path. In the planning space, the length of the calculated path is shorter and smoother than that using traditional APF method. In addition, the improved method can solve the dead point problem effectively.

Comparative aerial- and ground-based high-throughput phenotyping for the genetic dissection of NDVI as a proxy for drought-adaptive traits in durum wheat

USDA-ARS?s Scientific Manuscript database

High-throughput phenotyping platforms (HTPPs) provide novel opportunities to more effectively dissect the genetic basis of drought-adaptive traits. This genome-wide association study (GWAS) compares the results obtained with two Unmanned Aerial Vehicles (UAVs) and a ground-based platform used to mea...

Autonomous search and surveillance with small fixed wing aircraft

NASA Astrophysics Data System (ADS)

McGee, Timothy Garland

Small unmanned aerial vehicles (UAVs) have the potential to act as low cost tools in a variety of both civilian and military applications including traffic monitoring, border patrol, and search and rescue. While most current operational UAV systems require human operators, advances in autonomy will allow these systems to reach their full potential as sensor platforms. This dissertation specifically focuses on developing advanced control, path planning, search, and image processing techniques that allow small fixed wing aircraft to autonomously collect data. The problems explored were motivated by experience with the development and experimental flight testing of a fleet of small autonomous fixed wing aircraft. These issues, which have not been fully addressed in past work done on ground vehicles or autonomous helicopters, include the influence of wind and turning rate constraints, the non-negligible velocity of ground targets relative to the aircraft velocity, and limitations on sensor size and processing power on small vehicles. Several contributions for the autonomous operation of small fixed wing aircraft are presented. Several sliding surface controllers are designed which extend previous techniques to include variable sliding surface coefficients and the use of spatial vehicle dynamics. These advances eliminate potential singularities in the control laws to follow spatially defined paths and allow smooth transition between controllers. The optimal solution for the problem of path planning through an ordered set of points for an aircraft with a bounded turning rate in the presence of a constant wind is then discussed. Path planning strategies are also explored to guarantee that a searcher will travel within sensing distance of a mobile ground target. This work assumes only a maximum velocity of the target and is designed to succeed for any possible path of the target. Closed-loop approximations of both the path planning and search techniques, using the sliding surface controllers already discussed, are also studied. Finally, a novel method is presented to detect obstacles by segmenting an image into sky and non-sky regions. The feasibility of this method is demonstrated experimentally on an aircraft test bed.

New generation of human machine interfaces for controlling UAV through depth-based gesture recognition

NASA Astrophysics Data System (ADS)

Mantecón, Tomás.; del Blanco, Carlos Roberto; Jaureguizar, Fernando; García, Narciso

2014-06-01

New forms of natural interactions between human operators and UAVs (Unmanned Aerial Vehicle) are demanded by the military industry to achieve a better balance of the UAV control and the burden of the human operator. In this work, a human machine interface (HMI) based on a novel gesture recognition system using depth imagery is proposed for the control of UAVs. Hand gesture recognition based on depth imagery is a promising approach for HMIs because it is more intuitive, natural, and non-intrusive than other alternatives using complex controllers. The proposed system is based on a Support Vector Machine (SVM) classifier that uses spatio-temporal depth descriptors as input features. The designed descriptor is based on a variation of the Local Binary Pattern (LBP) technique to efficiently work with depth video sequences. Other major consideration is the especial hand sign language used for the UAV control. A tradeoff between the use of natural hand signs and the minimization of the inter-sign interference has been established. Promising results have been achieved in a depth based database of hand gestures especially developed for the validation of the proposed system.

Utilization of Unmanned Aerial Vehicles for Rangeland Resources Monitoring in a Changing Regulatory Environment (Invited)

NASA Astrophysics Data System (ADS)

Rango, A.; Vivoni, E. R.; Browning, D. M.; Anderson, C.; Laliberte, A. S.

2013-12-01

It is taking longer than expected to realize the immense potential of Unmanned Aerial Vehicles (UAVs)for civil applications due to the complexity of regulations being developed by the Federal Aviation Authority (FAA) that can be applied to both manned and unmanned flight in the National Airspace System (NAS). As a result, FAA has required that for all UAV flights in the NAS, an external pilot must maintain line-of-sight contact with the UAV. Properly trained observers must also be present to assist the external pilot in collision avoidance. Additionally, in order to fly in the NAS, formal approval must be requested from FAA through application for a Certificate of Authorization (COA for government applicants or a Special Airworthiness Certificate (SAC) in the experimental category for non-government applicants. Flight crews of UAVs must pass exams also required for manned airplane pilots. Although flight crews for UAVs are not required to become manned airplane pilots, UAV flight missions are much more efficient if one or two of the UAV flight crew are also manned aircraft pilots so they can serve as the UAV mission commander. Our group has performed numerous UAV flights within the Jornada Experimental Range in southern New Mexico. Two developments with Jornada UAVs can be recommended to other UAV operators that would increase flight time experience and study areas covered by UAV images. First, do not overlook the possibility of obtaining permission to fly in Restricted Military Airspace (RMA). At the Jornada, our airspace is approximately 50% NAS and 50% RMA. With experiments ongoing in both types of airspace, we can fly in both areas and continue to increase UAV flights. Second, we have developed an air- and-ground vehicle approach for long distance, continuous pilot transport that always maintains line-of-sight requirements. This allows flying several target areas on a single mission and increasing the number of acquired UAV images - over 90,000 UAV images have now been acquired at Jornada. Most of our UAV flights have taken place over rangelands or watersheds in the western U.S. These flights have been successful used for classification of vegetation cover and type, measuring gaps between vegetation patches, identifing locations of potentially erosive soil, deriving digital elevation models, and monitoring plant phenology.. These measurements can be directly compared to more costly and time-intensive traditional techniques used in rangeland health determinations. New UAVs are becoming available with increased sensor payload capacity. At Jornada we have concentrated on flying at low altitudes (~215 m) to acquire hyperspatial resolutions with digital cameras of about 5-6 cm. We also fly a six band multispectral camera with spatial resolution of ~ 13 cm. We have recently acquired a larger Bat-4 UAV to go with the Bat-3 UAV. The major improvement associated with this upgrade is an increase in sensor payload from 1.4 kg to 14 kg. We are surveying the type of sensors that we could add to best increase our information content.

Exploitation of Self Organization in UAV Swarms for Optimization in Combat Environments

DTIC Science & Technology

2008-03-01

behaviors and entangled hierarchy into Swarmfare [59] UAV simulation environment to include these models. • Validate this new model’s success through...Figure 4.3. The hierarchy of control emerges from the entangled hierarchy of the state relations at the simulation , swarm and rule/behaviors level...majors, major) Abstract Model Types (AMT) Figure A.1: SO Abstract Model Type Table 142 Appendix B. Simulators Comparision Name MATLAB Multi UAV MultiUAV

Pigeon interaction mode switch-based UAV distributed flocking control under obstacle environments.

PubMed

Qiu, Huaxin; Duan, Haibin

2017-11-01

Unmanned aerial vehicle (UAV) flocking control is a serious and challenging problem due to local interactions and changing environments. In this paper, a pigeon flocking model and a pigeon coordinated obstacle-avoiding model are proposed based on a behavior that pigeon flocks will switch between hierarchical and egalitarian interaction mode at different flight phases. Owning to the similarity between bird flocks and UAV swarms in essence, a distributed flocking control algorithm based on the proposed pigeon flocking and coordinated obstacle-avoiding models is designed to coordinate a heterogeneous UAV swarm to fly though obstacle environments with few informed individuals. The comparative simulation results are elaborated to show the feasibility, validity and superiority of our proposed algorithm. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

UAVs Being Used for Environmental Surveying

ScienceCinema

Chung, Sandra

2017-12-09

UAVs, are much more sophisticated than your typical remote-controlled plane. INL robotics and remote sensing experts have added state-of-the-art imaging and wireless technology to the UAVs to create intelligent remote surveillance craft that can rapidly survey a wide area for damage and track down security threats.

Multi-temporal UAV-borne LiDAR point clouds for vegetation analysis - a case study

NASA Astrophysics Data System (ADS)

Mandlburger, Gottfried; Wieser, Martin; Hollaus, Markus; Pfennigbauer, Martin; Riegl, Ursula

2016-04-01

In the recent past the introduction of compact and lightweight LiDAR (Light Detection And Ranging) sensors together with progress in UAV (Unmanned Aerial Vehicle) technology allowed the integration of laser scanners on remotely piloted multicopter, helicopter-type and even fixed-wing platforms. The multi-target capabilities of state-of-the-art time-of-flight full-waveform laser sensors operated from low flying UAV-platforms has enabled capturing of the entire 3D structure of semi-transparent objects like deciduous forests under leaf-off conditions in unprecedented density and completeness. For such environments it has already been demonstrated that UAV-borne laser scanning combines the advantages of terrestrial laser scanning (high point density, short range) and airborne laser scanning (bird's eye perspective, homogeneous point distribution). Especially the oblique looking capabilities of scanners with a large field of view (>180°) enable capturing of vegetation from different sides resulting in a constantly high point density also in the sub canopy domain. Whereas the findings stated above were drawn based on a case study carried out in February 2015 with the Riegl VUX-1UAV laser scanner system mounted on a Riegl RiCopter octocopter UAV-platform over an alluvial forest at the Pielach River (Lower Austria), the site was captured a second time with the same sensor system and mission parameters at the end of the vegetation period on October 28th, 2015. The main goal of this experiment was to assess the impact of the late autumn foliage on the achievable 3D point density. Especially the entire understory vegetation and certain tree species (e.g. willow) were still in full leaf whereas the bigger trees (poplar) where already partly defoliated. The comparison revealed that, although both campaigns featured virtually the same laser shot count, the ground point density dropped from 517 points/m2 in February (leaf-off) to 267 points/m2 end of October (leaf-on). The decrease of ca. 50% is compensated by an increase in the upper canopy area (>20 m a.g.l.; Feb: 348 points/m2, Oct: 757 points/m2, increase rate: 118%). The greater leaf area in October results in more laser echoes from the canopy but the density decrease on the ground is not entirely attributed to shadowing from the upper canopy as the point distribution is nearly constant in the medium (10-20 m) and lower (0-10 m) sub-canopy area. The lower density on the ground is rather caused by a densely foliated shrub layer (0.15-3 m; Feb: 178 points/m2, Oct: 259 points/m2, increase rate: 46%). A sharp ground point density drop could be observed in areas covered by an invasive weed species (Fallopia japonica) which keeps its extremely dense foliage till late in the year. In summary, the preliminary point density study has shown the potential of UAV-borne, multi-temporal LiDAR for characterization of seasonal vegetation changes in deciduous environments. It is remarkable that even under leaf-on conditions a very high terrain point density is achievable. Except for the dense shrub layer, the case study has shown a similar 3D point distribution in the sub-canopy area for leaf-off and leaf-on data acquisition.

Distributed autonomous systems: resource management, planning, and control algorithms

NASA Astrophysics Data System (ADS)

Smith, James F., III; Nguyen, ThanhVu H.

2005-05-01

Distributed autonomous systems, i.e., systems that have separated distributed components, each of which, exhibit some degree of autonomy are increasingly providing solutions to naval and other DoD problems. Recently developed control, planning and resource allocation algorithms for two types of distributed autonomous systems will be discussed. The first distributed autonomous system (DAS) to be discussed consists of a collection of unmanned aerial vehicles (UAVs) that are under fuzzy logic control. The UAVs fly and conduct meteorological sampling in a coordinated fashion determined by their fuzzy logic controllers to determine the atmospheric index of refraction. Once in flight no human intervention is required. A fuzzy planning algorithm determines the optimal trajectory, sampling rate and pattern for the UAVs and an interferometer platform while taking into account risk, reliability, priority for sampling in certain regions, fuel limitations, mission cost, and related uncertainties. The real-time fuzzy control algorithm running on each UAV will give the UAV limited autonomy allowing it to change course immediately without consulting with any commander, request other UAVs to help it, alter its sampling pattern and rate when observing interesting phenomena, or to terminate the mission and return to base. The algorithms developed will be compared to a resource manager (RM) developed for another DAS problem related to electronic attack (EA). This RM is based on fuzzy logic and optimized by evolutionary algorithms. It allows a group of dissimilar platforms to use EA resources distributed throughout the group. For both DAS types significant theoretical and simulation results will be presented.

Multimodal UAV detection: study of various intrusion scenarios

NASA Astrophysics Data System (ADS)

Hengy, Sebastien; Laurenzis, Martin; Schertzer, Stéphane; Hommes, Alexander; Kloeppel, Franck; Shoykhetbrod, Alex; Geibig, Thomas; Johannes, Winfried; Rassy, Oussama; Christnacher, Frank

2017-10-01

Small unmanned aerial vehicles (UAVs) are becoming increasingly popular and affordable the last years for professional and private consumer market, with varied capacities and performances. Recent events showed that illicit or hostile uses constitute an emergent, quickly evolutionary threat. Recent developments in UAV technologies tend to bring autonomous, highly agile and capable unmanned aerial vehicles to the market. These UAVs can be used for spying operations as well as for transporting illicit or hazardous material (smuggling, flying improvised explosive devices). The scenario of interest concerns the protection of sensitive zones against the potential threat constituted by small drones. In the recent past, field trials were carried out to investigate the detection and tracking of multiple UAV flying at low altitude. Here, we present results which were achieved using a heterogeneous sensor network consisting of acoustic antennas, small FMCW RADAR systems and optical sensors. While acoustics and RADAR was applied to monitor a wide azimuthal area (360°), optical sensors were used for sequentially identification. The localization results have been compared to the ground truth data to estimate the efficiency of each detection system. Seven-microphone acoustic arrays allow single source localization. The mean azimuth and elevation estimation error has been measured equal to 1.5 and -2.5 degrees respectively. The FMCW radar allows tracking of multiple UAVs by estimating their range, azimuth and motion speed. Both technologies can be linked to the electro-optical system for final identification of the detected object.

Pricise Target Geolocation and Tracking Based on Uav Video Imagery

NASA Astrophysics Data System (ADS)

Hosseinpoor, H. R.; Samadzadegan, F.; Dadrasjavan, F.

2016-06-01

There is an increasingly large number of applications for Unmanned Aerial Vehicles (UAVs) from monitoring, mapping and target geolocation. However, most of commercial UAVs are equipped with low-cost navigation sensors such as C/A code GPS and a low-cost IMU on board, allowing a positioning accuracy of 5 to 10 meters. This low accuracy cannot be used in applications that require high precision data on cm-level. This paper presents a precise process for geolocation of ground targets based on thermal video imagery acquired by small UAV equipped with RTK GPS. The geolocation data is filtered using an extended Kalman filter, which provides a smoothed estimate of target location and target velocity. The accurate geo-locating of targets during image acquisition is conducted via traditional photogrammetric bundle adjustment equations using accurate exterior parameters achieved by on board IMU and RTK GPS sensors, Kalman filtering and interior orientation parameters of thermal camera from pre-flight laboratory calibration process. The results of this study compared with code-based ordinary GPS, indicate that RTK observation with proposed method shows more than 10 times improvement of accuracy in target geolocation.

Exploratory use of a UAV platform for variety selection in peanut

NASA Astrophysics Data System (ADS)

Balota, Maria; Oakes, Joseph

2016-05-01

Variety choice is the most important production decision farmers make because high yielding varieties can increase profit with no additional production costs. Therefore, yield improvement has been the major objective for peanut (Arachis hypogaea L.) breeding programs worldwide, but the current breeding approach (selecting for yield under optimal production conditions) is slow and inconsistent with the needs derived from population demand and climate change. To improve the rate of genetic gain, breeders have used target physiological traits such as leaf chlorophyll content using SPAD chlorophyll meter, Normalized Difference Vegetation Index (NDVI) from canopy reflectance in visible and near infra-red (NIR) wavelength bands, and canopy temperature (CT) manually measured with infra-red (IR) thermometers at the canopy level; but its use for routine selection was hampered by the time required to walk hundreds of plots. Recent developments in remote sensing-based high throughput phenotyping platforms using unmanned aerial vehicles (UAV) have shown good potential for future breeding advancements. Recently, we initiated a study for the evaluation of suitability of digital imagery, NDVI, and CT taken from an UAV platform for peanut variety differentiation. Peanut is unique for setting its yield underground and resilience to drought and heat, for which yield is difficult to pre-harvest estimate; although the need for early yield estimation within the breeding programs exists. Twenty-six peanut cultivars and breeding lines were grown in replicated plots either optimally or deficiently irrigated under rain exclusion shelters at Suffolk, Virginia. At the beginning maturity growth stage, approximately a month before digging, NDVI and CT were taken with ground-based sensors at the same time with red, blue, green (RGB) images from a Sony camera mounted on an UAV platform. Disease ratings were also taken pre-harvest. Ground and UAV derived vegetation indices were analyzed for disease and yield prediction and further presented in this paper.

Integrating Unmanned Aerial Vehicles and Terrestrial Structure from Motion Photogrammetry for Assessing High Mountain Glacier Change, Huaytapallana, Peru

NASA Astrophysics Data System (ADS)

Wigmore, O.; Mark, B. G.; Lagos, P.; Somers, L. D.; McKenzie, J. M.; Huh, K. I.; Hopkinson, C.; Baraer, M.; Crumley, R. L.

2016-12-01

Terrestrial photogrammetry has a long and successful history of application to glaciological research. However, traditional methods rely upon large and expensive metric cameras and detailed triangulation of in-scene points for derivation of terrain models and analysis of glacier change. Recent developments in computer vision, including the advent of Structure from Motion (SfM) algorithms and associated software packages have made it possible to use consumer grade digital cameras to produce highly precise digital elevation models. This has facilitated the rapid expansion of unmanned aerial vehicles (UAVs) for mapping purposes. However, without onboard RTK GNSS positions of the UAV, within scene survey-grade ground targets are required for accurate georectification. Gaining access to mountain glaciers for the installation and survey of ground targets is often labour intensive, hazardous and sometimes impossible. Compounding this are limitations of UAV flight within these confined and high elevation locations and reduced flight times that limit the total survey area. Luckily, these environments also present a highly suitable location for the application of terrestrial SfM photogrammetry; because; high moraines, cliffs and ridgelines provide excellent 'semi-nadir' viewing of the glacier surface; while steep mountain walls present a close to nadir view from an oblique angle. In this study we present a workflow and results from an integrated UAV and terrestrial SfM photogrammetry campaign at Huaytapallana glacier, Huancayo Peru. We combined terrestrial images taken from GNSS surveyed positions with oblique UAV imagery of the mountain face. From this data a centimetre resolution orthomosaic and a decimetre resolution DEM of the snow and ice covered mountain face and proglacial lake were generated, covering over 6km2. Accuracy of the surface was determined from comparison over ice free areas to 1m aerial LiDAR data collected in 2009. Changes in glacier volume were then determined through DEM differencing with the LiDAR data.

Using UAV photogrammetry to study topographic change: application to Saskatchewan Glacier, Alberta, Canada

NASA Astrophysics Data System (ADS)

Meunier Cardinal, G.; Demuth, M. N.; Kinnard, C.

2016-12-01

Glaciers are an important source of fresh water in the headwaters of the Canadian Rocky Mountains, and ongoing climate warming could reduce their future hydrological contribution. Unmanned Aerial Vehicles UAVs) are an emergent technology that allow studying glacial processes with an unprecedented level of detail, but their usefulness for deriving accurate topographic data on glaciers has not yet been fully assessed. In this perspective we tested the use of a UAV platform to acquire images at a very high spatial resolution (<10cm) in order to estimate topographical and dynamic changes over a one year period on the ablation zone of Saskatchewan glacier, the main outlet of the Columbia Icefield in Alberta, Canada (52°06N, 117°15W). Two data acquisition campaigns were carried out, in August 2014 and 2015. Orthomosaics and digital elevation models (DEMs) with a high spatial resolution (<10cm) were produced for each year, using the Structure from Motion (SfM) algorithm. A detailed assessment of DEM errors was performed by cross-validation of an network of ground control points (GCPs) deployed on the glacier surface. The influence of checkpoint position in the network, border effects, number of photos calibrated and GPS accuracy were examined. Topographical changes were measured from the DEM difference and surface displacements estimated by applying feature tracking techniques to the orthomosaics. Further, the dominant scales of topographic spatial variability were examined using a semivariogram analysis of the DEMs. Results show that UAV-based photogrammetry is promising to further our understanding of high-resolution glacier surface processes and to perform repeat, on-demand monitoring of glacier changes, but their application on remote glaciers remains challenging.

High spatial resolution mapping of folds and fractures using Unmanned Aerial Vehicle (UAV) photogrammetry

NASA Astrophysics Data System (ADS)

Cruden, A. R.; Vollgger, S.

2016-12-01

The emerging capability of UAV photogrammetry combines a simple and cost-effective method to acquire digital aerial images with advanced computer vision algorithms that compute spatial datasets from a sequence of overlapping digital photographs from various viewpoints. Depending on flight altitude and camera setup, sub-centimeter spatial resolution orthophotographs and textured dense point clouds can be achieved. Orientation data can be collected for detailed structural analysis by digitally mapping such high-resolution spatial datasets in a fraction of time and with higher fidelity compared to traditional mapping techniques. Here we describe a photogrammetric workflow applied to a structural study of folds and fractures within alternating layers of sandstone and mudstone at a coastal outcrop in SE Australia. We surveyed this location using a downward looking digital camera mounted on commercially available multi-rotor UAV that autonomously followed waypoints at a set altitude and speed to ensure sufficient image overlap, minimum motion blur and an appropriate resolution. The use of surveyed ground control points allowed us to produce a geo-referenced 3D point cloud and an orthophotograph from hundreds of digital images at a spatial resolution < 10 mm per pixel, and cm-scale location accuracy. Orientation data of brittle and ductile structures were semi-automatically extracted from these high-resolution datasets using open-source software. This resulted in an extensive and statistically relevant orientation dataset that was used to 1) interpret the progressive development of folds and faults in the region, and 2) to generate a 3D structural model that underlines the complex internal structure of the outcrop and quantifies spatial variations in fold geometries. Overall, our work highlights how UAV photogrammetry can contribute to new insights in structural analysis.

UAV applications for thermodynamic profiling: Emphasis on ice fog research

NASA Astrophysics Data System (ADS)

Gultepe, Ismail; Heymsfield, Andrew J.; Fernando, Harindra J. S.; Hoch, Sebastian W.; Ware, Randolph

2016-04-01

Ice fog occurs often over the Arctic, cold climatic, and mountainous regions for about 30% of time where temperature (T) can go down to -10°C or below. Ice Nucleation (IN) and cooling processes play an important role by the controlling the intensity of ice fog conditions that affect aviation application, transportation, and local climate. Ice fog can also occur at T above -10°C but close to 0°C it occurs due to freezing of supercooled droplets that include an IN. To better document ice fog conditions, observations from the ice fog events of the Indirect and Semi-Direct Aerosol effects on Climate (ISDAC) project, Barrow, Alaska, Fog Remote Sensing And Modeling (FRAM) project Yellowknife, Northwest Territories, and the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) project, Heber City, Utah, were analyzed.. Measurements difficulties of small ice fog particles at cold temperatures and low-level flying restrictions prevent observations from aircraft within the surface boundary layer. However, unmanned Aerial Vehicles (UAVs) can be operated safely to measure IN number concentration, Relative Humidity with respect to ice (RHi), T, horizontal wind speed (Uh) and direction, and ice crystal spectra less than about 500 micron. Thermodynamic profiling by a Radiometrics Profiling Microwave Radiometer (PMWR) and Vaisala CL51 ceilometer was used to describe ice fog conditions in the vertical and its time development. In this presentation, ice fog characteristics and its thermodynamic environment will be presented using both ground-based and airborne platforms such as a UAV with new sensors. Some examples of measurements from the UAV for future research, and challenges related to both ice fog measurements and visibility parameterization will also be presented.

Calculating e-flow using UAV and ground monitoring

NASA Astrophysics Data System (ADS)

Zhao, C. S.; Zhang, C. B.; Yang, S. T.; Liu, C. M.; Xiang, H.; Sun, Y.; Yang, Z. Y.; Zhang, Y.; Yu, X. Y.; Shao, N. F.; Yu, Q.

2017-09-01

Intense human activity has led to serious degradation of basin water ecosystems and severe reduction in the river flow available for aquatic biota. As an important water ecosystem index, environmental flows (e-flows) are crucial for maintaining sustainability. However, most e-flow measurement methods involve long cycles, low efficiency, and transdisciplinary expertise. This makes it impossible to rapidly assess river e-flows at basin or larger scales. This study presents a new method to rapidly assessing e-flows coupling UAV and ground monitorings. UAV was firstly used to calculate river-course cross-sections with high-resolution stereoscopic images. A dominance index was then used to identify key fish species. Afterwards a habitat suitability index, along with biodiversity and integrity indices, was used to determine an appropriate flow velocity with full consideration of the fish spawning period. The cross-sections and flow velocity values were then combined into AEHRA, an e-flow assessment method for studying e-flows and supplying-rate. To verify the results from this new method, the widely used Tennant method was employed. The root-mean-square errors of river cross-sections determined by UAV are less than 0.25 m, which constitutes 3-5% water-depth of the river cross-sections. In the study area of Jinan city, the ecological flow velocity (VE) is equal to or greater than 0.11 m/s, and the ecological water depth (HE) is greater than 0.8 m. The river ecosystem is healthy with the minimum e-flow requirements being always met when it is close to large rivers, which is beneficial for the sustainable development of the water ecosystem. In the south river channel of Jinan, the upstream flow mostly meets the minimum e-flow requirements, and the downstream flow always meets the minimum e-flow requirements. The north of Jinan consists predominantly of artificial river channels used for irrigation. Rainfall rarely meets the minimum e-flow and irrigation water requirements. We suggest that the water shortage problem can be partly solved by diversion of the Yellow River. These results can provide useful information for ecological operations and restoration. The method used in this study for calculating e-flow based on a combination of UAV and ground monitoring can effectively promote research progress into basin e-flow, and provide an important reference for e-flow monitoring around the world.

A Novel Method for Vertical Acceleration Noise Suppression of a Thrust-Vectored VTOL UAV.

PubMed

Li, Huanyu; Wu, Linfeng; Li, Yingjie; Li, Chunwen; Li, Hangyu

2016-12-02

Acceleration is of great importance in motion control for unmanned aerial vehicles (UAVs), especially during the takeoff and landing stages. However, the measured acceleration is inevitably polluted by severe noise. Therefore, a proper noise suppression procedure is required. This paper presents a novel method to reduce the noise in the measured vertical acceleration for a thrust-vectored tail-sitter vertical takeoff and landing (VTOL) UAV. In the new procedure, a Kalman filter is first applied to estimate the UAV mass by using the information in the vertical thrust and measured acceleration. The UAV mass is then used to compute an estimate of UAV vertical acceleration. The estimated acceleration is finally fused with the measured acceleration to obtain the minimum variance estimate of vertical acceleration. By doing this, the new approach incorporates the thrust information into the acceleration estimate. The method is applied to the data measured in a VTOL UAV takeoff experiment. Two other denoising approaches developed by former researchers are also tested for comparison. The results demonstrate that the new method is able to suppress the acceleration noise substantially. It also maintains the real-time performance in the final estimated acceleration, which is not seen in the former denoising approaches. The acceleration treated with the new method can be readily used in the motion control applications for UAVs to achieve improved accuracy.

A Novel Method for Vertical Acceleration Noise Suppression of a Thrust-Vectored VTOL UAV

PubMed Central

Li, Huanyu; Wu, Linfeng; Li, Yingjie; Li, Chunwen; Li, Hangyu

2016-01-01

Acceleration is of great importance in motion control for unmanned aerial vehicles (UAVs), especially during the takeoff and landing stages. However, the measured acceleration is inevitably polluted by severe noise. Therefore, a proper noise suppression procedure is required. This paper presents a novel method to reduce the noise in the measured vertical acceleration for a thrust-vectored tail-sitter vertical takeoff and landing (VTOL) UAV. In the new procedure, a Kalman filter is first applied to estimate the UAV mass by using the information in the vertical thrust and measured acceleration. The UAV mass is then used to compute an estimate of UAV vertical acceleration. The estimated acceleration is finally fused with the measured acceleration to obtain the minimum variance estimate of vertical acceleration. By doing this, the new approach incorporates the thrust information into the acceleration estimate. The method is applied to the data measured in a VTOL UAV takeoff experiment. Two other denoising approaches developed by former researchers are also tested for comparison. The results demonstrate that the new method is able to suppress the acceleration noise substantially. It also maintains the real-time performance in the final estimated acceleration, which is not seen in the former denoising approaches. The acceleration treated with the new method can be readily used in the motion control applications for UAVs to achieve improved accuracy. PMID:27918422

Uav Photogrammetry with Oblique Images: First Analysis on Data Acquisition and Processing

NASA Astrophysics Data System (ADS)

Aicardi, I.; Chiabrando, F.; Grasso, N.; Lingua, A. M.; Noardo, F.; Spanò, A.

2016-06-01

In recent years, many studies revealed the advantages of using airborne oblique images for obtaining improved 3D city models (e.g. including façades and building footprints). Expensive airborne cameras, installed on traditional aerial platforms, usually acquired the data. The purpose of this paper is to evaluate the possibility of acquire and use oblique images for the 3D reconstruction of a historical building, obtained by UAV (Unmanned Aerial Vehicle) and traditional COTS (Commercial Off-the-Shelf) digital cameras (more compact and lighter than generally used devices), for the realization of high-level-of-detail architectural survey. The critical issues of the acquisitions from a common UAV (flight planning strategies, ground control points, check points distribution and measurement, etc.) are described. Another important considered aspect was the evaluation of the possibility to use such systems as low cost methods for obtaining complete information from an aerial point of view in case of emergency problems or, as in the present paper, in the cultural heritage application field. The data processing was realized using SfM-based approach for point cloud generation: different dense image-matching algorithms implemented in some commercial and open source software were tested. The achieved results are analysed and the discrepancies from some reference LiDAR data are computed for a final evaluation. The system was tested on the S. Maria Chapel, a part of the Novalesa Abbey (Italy).

Uav-Mapping - a User Report

NASA Astrophysics Data System (ADS)

Mayr, W.

2011-09-01

This paper reports on first hand experiences in operating an unmanned airborne system (UAS) for mapping purposes in the environment of a mapping company. Recently, a multitude of activities in UAVs is visible, and there is growing interest in the commercial, industrial, and academic mapping user communities and not only in those. As an introduction, the major components of an UAS are identified. The paper focuses on a 1.1kg UAV which is integrated and gets applied on a day-to-day basis as part of an UAS in standard aerial imaging tasks for more than two years already. We present the unmanned airborne vehicle in some detail as well as the overall system components such as autopilot, ground station, flight mission planning and control, and first level image processing. The paper continues with reporting on experiences gained in setting up constraints such a system needs to fulfill. Further on, operational aspects with emphasis on unattended flight mission mode are presented. Various examples show the applicability of UAS in geospatial tasks, proofing that UAS are capable delivering reliably e.g. orthomosaics, digital surface models and more. Some remarks on achieved accuracies give an idea on obtainable qualities. A discussion about safety features puts some light on important matters when entering unmanned flying activities and rounds up this paper. Conclusions summarize the state of the art of an operational UAS from the point of the view of the author.

Hydrology with unmanned aerial vehicles (UAVs)

USDA-ARS?s Scientific Manuscript database

Hydrologic remote sensing currently depends on expensive and infrequent aircraft observations for validation of operational satellite products, typically conducted during field campaigns that also include ground-based measurements. With the advent of new, hydrologically-relevant satellite missions, ...

Mission control of multiple unmanned aerial vehicles: a workload analysis.

PubMed

Dixon, Stephen R; Wickens, Christopher D; Chang, Dervon

2005-01-01

With unmanned aerial vehicles (UAVs), 36 licensed pilots flew both single-UAV and dual-UAV simulated military missions. Pilots were required to navigate each UAV through a series of mission legs in one of the following three conditions: a baseline condition, an auditory autoalert condition, and an autopilot condition. Pilots were responsible for (a) mission completion, (b) target search, and (c) systems monitoring. Results revealed that both the autoalert and the autopilot automation improved overall performance by reducing task interference and alleviating workload. The autoalert system benefited performance both in the automated task and mission completion task, whereas the autopilot system benefited performance in the automated task, the mission completion task, and the target search task. Practical implications for the study include the suggestion that reliable automation can help alleviate task interference and reduce workload, thereby allowing pilots to better handle concurrent tasks during single- and multiple-UAV flight control.

Estimating snow depth in real time using unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Niedzielski, Tomasz; Mizinski, Bartlomiej; Witek, Matylda; Spallek, Waldemar; Szymanowski, Mariusz

2016-04-01

In frame of the project no. LIDER/012/223/L-5/13/NCBR/2014, financed by the National Centre for Research and Development of Poland, we elaborated a fully automated approach for estimating snow depth in real time in the field. The procedure uses oblique aerial photographs taken by the unmanned aerial vehicle (UAV). The geotagged images of snow-covered terrain are processed by the Structure-from-Motion (SfM) method which is used to produce a non-georeferenced dense point cloud. The workflow includes the enhanced RunSFM procedure (keypoint detection using the scale-invariant feature transform known as SIFT, image matching, bundling using the Bundler, executing the multi-view stereo PMVS and CMVS2 software) which is preceded by multicore image resizing. The dense point cloud is subsequently automatically georeferenced using the GRASS software, and the ground control points are borrowed from positions of image centres acquired from the UAV-mounted GPS receiver. Finally, the digital surface model (DSM) is produced which - to improve the accuracy of georeferencing - is shifted using a vector obtained through precise geodetic GPS observation of a single ground control point (GCP) placed on the Laboratory for Unmanned Observations of Earth (mobile lab established at the University of Wroclaw, Poland). The DSM includes snow cover and its difference with the corresponding snow-free DSM or digital terrain model (DTM), following the concept of the digital elevation model of differences (DOD), produces a map of snow depth. Since the final result depends on the snow-free model, two experiments are carried out. Firstly, we show the performance of the entire procedure when the snow-free model reveals a very high resolution (3 cm/px) and is produced using the UAV-taken photographs and the precise GCPs measured by the geodetic GPS receiver. Secondly, we perform a similar exercise but the 1-metre resolution light detection and ranging (LIDAR) DSM or DTM serves as the snow-free model. Thus, the main objective of the paper is to present the performance of the new procedure for estimating snow depth and to compare the two experiments.

Unsupervised learning in persistent sensing for target recognition by wireless ad hoc networks of ground-based sensors

NASA Astrophysics Data System (ADS)

Hortos, William S.

2008-04-01

In previous work by the author, effective persistent and pervasive sensing for recognition and tracking of battlefield targets were seen to be achieved, using intelligent algorithms implemented by distributed mobile agents over a composite system of unmanned aerial vehicles (UAVs) for persistence and a wireless network of unattended ground sensors for pervasive coverage of the mission environment. While simulated performance results for the supervised algorithms of the composite system are shown to provide satisfactory target recognition over relatively brief periods of system operation, this performance can degrade by as much as 50% as target dynamics in the environment evolve beyond the period of system operation in which the training data are representative. To overcome this limitation, this paper applies the distributed approach using mobile agents to the network of ground-based wireless sensors alone, without the UAV subsystem, to provide persistent as well as pervasive sensing for target recognition and tracking. The supervised algorithms used in the earlier work are supplanted by unsupervised routines, including competitive-learning neural networks (CLNNs) and new versions of support vector machines (SVMs) for characterization of an unknown target environment. To capture the same physical phenomena from battlefield targets as the composite system, the suite of ground-based sensors can be expanded to include imaging and video capabilities. The spatial density of deployed sensor nodes is increased to allow more precise ground-based location and tracking of detected targets by active nodes. The "swarm" mobile agents enabling WSN intelligence are organized in a three processing stages: detection, recognition and sustained tracking of ground targets. Features formed from the compressed sensor data are down-selected according to an information-theoretic algorithm that reduces redundancy within the feature set, reducing the dimension of samples used in the target recognition and tracking routines. Target tracking is based on simplified versions of Kalman filtration. Accuracy of recognition and tracking of implemented versions of the proposed suite of unsupervised algorithms is somewhat degraded from the ideal. Target recognition and tracking by supervised routines and by unsupervised SVM and CLNN routines in the ground-based WSN is evaluated in simulations using published system values and sensor data from vehicular targets in ground-surveillance scenarios. Results are compared with previously published performance for the system of the ground-based sensor network (GSN) and UAV swarm.

Feature-Based Approach for the Registration of Pushbroom Imagery with Existing Orthophotos

NASA Astrophysics Data System (ADS)

Xiong, Weifeng

Low-cost Unmanned Airborne Vehicles (UAVs) are rapidly becoming suitable platforms for acquiring remote sensing data for a wide range of applications. For example, a UAV-based mobile mapping system (MMS) is emerging as a novel phenotyping tool that delivers several advantages to alleviate the drawbacks of conventional manual plant trait measurements. Moreover, UAVs equipped with direct geo-referenced frame cameras and pushbroom scanners can acquire geospatial data for comprehensive high-throughput phenotyping. UAVs for mobile mapping platforms are low-cost and easy to use, can fly closer to the objects, and are filling an important gap between ground wheel-based and traditional manned-airborne platforms. However, consumer-grade UAVs are capable of carrying only equipment with a relatively light payload and their flying time is determined by a limited battery life. These restrictions of UAVs unfortunately force potential users to adopt lower-quality direct geo-referencing and imaging systems that may negatively impact the quality of the deliverables. Recent advances in sensor calibration and automated triangulation have made it feasible to obtain accurate mapping using low-cost camera systems equipped with consumer-grade GNSS/INS units. However, ortho-rectification of the data from a linear-array scanner is challenging for low-cost UAV systems, because the derived geo-location information from pushbroom sensors is quite sensitive to the performance of the implemented direct geo-referencing unit. This thesis presents a novel approach for improving the ortho-rectification of hyperspectral pushbroom scanner imagery with the aid of orthophotos generated from frame cameras through the identification of conjugate features while modeling the impact of residual artifacts in the direct geo-referencing information. The experimental results qualitatively and quantitatively proved the feasibility of the proposed methodology in improving the geo-referencing accuracy of real datasets collected over an agricultural field.

Aeromagnetic Compensation for UAVs

NASA Astrophysics Data System (ADS)

Naprstek, T.; Lee, M. D.

2017-12-01

Aeromagnetic data is one of the most widely collected types of data in exploration geophysics. With the continuing prevalence of unmanned air vehicles (UAVs) in everyday life there is a strong push for aeromagnetic data collection using UAVs. However, apart from the many political and legal barriers to overcome in the development of UAVs as aeromagnetic data collection platforms, there are also significant scientific hurdles, primary of which is magnetic compensation. This is a well-established process in manned aircraft achieved through a combination of platform magnetic de-noising and compensation routines. However, not all of this protocol can be directly applied to UAVs due to fundamental differences in the platforms, most notably the decrease in scale causing magnetometers to be significantly closer to the avionics. As such, the methodology must be suitably adjusted. The National Research Council of Canada has collaborated with Aeromagnetic Solutions Incorporated to develop a standardized approach to de-noising and compensating UAVs, which is accomplished through a series of static and dynamic experiments. On the ground, small static tests are conducted on individual components to determine their magnetization. If they are highly magnetic, they are removed, demagnetized, or characterized such that they can be accounted for in the compensation. Dynamic tests can include measuring specific components as they are powered on and off to assess their potential effect on airborne data. The UAV is then flown, and a modified compensation routine is applied. These modifications include utilizing onboard autopilot current sensors as additional terms in the compensation algorithm. This process has been applied with success to fixed-wing and rotary-wing platforms, with both a standard manned-aircraft magnetometer, as well as a new atomic magnetometer, much smaller in scale.

Intercomparison of Unmanned Aerial Vehicle and Ground-Based Narrow Band Spectrometers Applied to Crop Trait Monitoring in Organic Potato Production

PubMed Central

Domingues Franceschini, Marston Héracles; Bartholomeus, Harm; van Apeldoorn, Dirk; Suomalainen, Juha; Kooistra, Lammert

2017-01-01

Vegetation properties can be estimated using optical sensors, acquiring data on board of different platforms. For instance, ground-based and Unmanned Aerial Vehicle (UAV)-borne spectrometers can measure reflectance in narrow spectral bands, while different modelling approaches, like regressions fitted to vegetation indices, can relate spectra with crop traits. Although monitoring frameworks using multiple sensors can be more flexible, they may result in higher inaccuracy due to differences related to the sensors characteristics, which can affect information sampling. Also organic production systems can benefit from continuous monitoring focusing on crop management and stress detection, but few studies have evaluated applications with this objective. In this study, ground-based and UAV spectrometers were compared in the context of organic potato cultivation. Relatively accurate estimates were obtained for leaf chlorophyll (RMSE = 6.07 µg·cm−2), leaf area index (RMSE = 0.67 m2·m−2), canopy chlorophyll (RMSE = 0.24 g·m−2) and ground cover (RMSE = 5.5%) using five UAV-based data acquisitions, from 43 to 99 days after planting. These retrievals are slightly better than those derived from ground-based measurements (RMSE = 7.25 µg·cm−2, 0.85 m2·m−2, 0.28 g·m−2 and 6.8%, respectively), for the same period. Excluding observations corresponding to the first acquisition increased retrieval accuracy and made outputs more comparable between sensors, due to relatively low vegetation cover on this date. Intercomparison of vegetation indices indicated that indices based on the contrast between spectral bands in the visible and near-infrared, like OSAVI, MCARI2 and CIg provided, at certain extent, robust outputs that could be transferred between sensors. Information sampling at plot level by both sensing solutions resulted in comparable discriminative potential concerning advanced stages of late blight incidence. These results indicate that optical sensors, and their integration, have great potential for monitoring this specific organic cropping system. PMID:28629159

Intercomparison of Unmanned Aerial Vehicle and Ground-Based Narrow Band Spectrometers Applied to Crop Trait Monitoring in Organic Potato Production.

PubMed

Domingues Franceschini, Marston Héracles; Bartholomeus, Harm; van Apeldoorn, Dirk; Suomalainen, Juha; Kooistra, Lammert

2017-06-18

Vegetation properties can be estimated using optical sensors, acquiring data on board of different platforms. For instance, ground-based and Unmanned Aerial Vehicle (UAV)-borne spectrometers can measure reflectance in narrow spectral bands, while different modelling approaches, like regressions fitted to vegetation indices, can relate spectra with crop traits. Although monitoring frameworks using multiple sensors can be more flexible, they may result in higher inaccuracy due to differences related to the sensors characteristics, which can affect information sampling. Also organic production systems can benefit from continuous monitoring focusing on crop management and stress detection, but few studies have evaluated applications with this objective. In this study, ground-based and UAV spectrometers were compared in the context of organic potato cultivation. Relatively accurate estimates were obtained for leaf chlorophyll (RMSE = 6.07 µg·cm -2 ), leaf area index (RMSE = 0.67 m²·m -2 ), canopy chlorophyll (RMSE = 0.24 g·m -2 ) and ground cover (RMSE = 5.5%) using five UAV-based data acquisitions, from 43 to 99 days after planting. These retrievals are slightly better than those derived from ground-based measurements (RMSE = 7.25 µg·cm -2 , 0.85 m²·m -2 , 0.28 g·m -2 and 6.8%, respectively), for the same period. Excluding observations corresponding to the first acquisition increased retrieval accuracy and made outputs more comparable between sensors, due to relatively low vegetation cover on this date. Intercomparison of vegetation indices indicated that indices based on the contrast between spectral bands in the visible and near-infrared, like OSAVI, MCARI2 and CI g provided, at certain extent, robust outputs that could be transferred between sensors. Information sampling at plot level by both sensing solutions resulted in comparable discriminative potential concerning advanced stages of late blight incidence. These results indicate that optical sensors, and their integration, have great potential for monitoring this specific organic cropping system.

Guidance and control for an autonomous soaring UAV

NASA Technical Reports Server (NTRS)

Allen, Michael J. (Inventor)

2008-01-01

The present invention provides a practical method for UAVs to take advantage of thermals in a manner similar to piloted aircrafts and soaring birds. In general, the invention is a method for a UAV to autonomously locate a thermal and be guided to the thermal to greatly improve range and endurance of the aircraft.

Energy extraction from atmospheric turbulence to improve flight vehicle performance

NASA Astrophysics Data System (ADS)

Patel, Chinmay Karsandas

Small 'bird-sized' Unmanned Aerial Vehicles (UAVs) have now become practical due to technological advances in embedded electronics, miniature sensors and actuators, and propulsion systems. Birds are known to take advantage of wind currents to conserve energy and fly long distances without flapping their wings. This dissertation explores the possibility of improving the performance of small UAVs by extracting the energy available in atmospheric turbulence. An aircraft can gain energy from vertical gusts by increasing its lift in regions of updraft and reducing its lift in downdrafts - a concept that has been known for decades. Starting with a simple model of a glider flying through a sinusoidal gust, a parametric optimization approach is used to compute the minimum gust amplitude and optimal control input required for the glider to sustain flight without losing energy. For small UAVs using optimal control inputs, sinusoidal gusts with amplitude of 10--15% of the cruise speed are sufficient to keep the aircraft aloft. The method is then modified and extended to include random gusts that are representative of natural turbulence. A procedure to design optimal control laws for energy extraction from realistic gust profiles is developed using a Genetic Algorithm (GA). A feedback control law is designed to perform well over a variety of random gusts, and not be tailored for one particular gust. A small UAV flying in vertical turbulence is shown to obtain average energy savings of 35--40% with the use of a simple control law. The design procedure is also extended to determine optimal control laws for sinusoidal as well as turbulent lateral gusts. The theoretical work is complemented by experimental validation using a small autonomous UAV. The development of a lightweight autopilot and UAV platform is presented. Flight test results show that active control of the lift of an autonomous glider resulted in approximately 46% average energy savings compared to glides with fixed control surfaces. Statistical analysis of test samples shows that 19% of the active control test runs resulted in no energy loss, thus demonstrating the potential of the 'gust soaring' concept to dramatically improve the performance of small UAVs.

UAVs and Machine Learning Revolutionising Invasive Grass and Vegetation Surveys in Remote Arid Lands.

PubMed

Sandino, Juan; Gonzalez, Felipe; Mengersen, Kerrie; Gaston, Kevin J

2018-02-16

The monitoring of invasive grasses and vegetation in remote areas is challenging, costly, and on the ground sometimes dangerous. Satellite and manned aircraft surveys can assist but their use may be limited due to the ground sampling resolution or cloud cover. Straightforward and accurate surveillance methods are needed to quantify rates of grass invasion, offer appropriate vegetation tracking reports, and apply optimal control methods. This paper presents a pipeline process to detect and generate a pixel-wise segmentation of invasive grasses, using buffel grass (Cenchrus ciliaris) and spinifex (Triodia sp.) as examples. The process integrates unmanned aerial vehicles (UAVs) also commonly known as drones, high-resolution red, green, blue colour model (RGB) cameras, and a data processing approach based on machine learning algorithms. The methods are illustrated with data acquired in Cape Range National Park, Western Australia (WA), Australia, orthorectified in Agisoft Photoscan Pro, and processed in Python programming language, scikit-learn, and eXtreme Gradient Boosting (XGBoost) libraries. In total, 342,626 samples were extracted from the obtained data set and labelled into six classes. Segmentation results provided an individual detection rate of 97% for buffel grass and 96% for spinifex, with a global multiclass pixel-wise detection rate of 97%. Obtained results were robust against illumination changes, object rotation, occlusion, background cluttering, and floral density variation.

UAVs and Machine Learning Revolutionising Invasive Grass and Vegetation Surveys in Remote Arid Lands

PubMed Central

2018-01-01

The monitoring of invasive grasses and vegetation in remote areas is challenging, costly, and on the ground sometimes dangerous. Satellite and manned aircraft surveys can assist but their use may be limited due to the ground sampling resolution or cloud cover. Straightforward and accurate surveillance methods are needed to quantify rates of grass invasion, offer appropriate vegetation tracking reports, and apply optimal control methods. This paper presents a pipeline process to detect and generate a pixel-wise segmentation of invasive grasses, using buffel grass (Cenchrus ciliaris) and spinifex (Triodia sp.) as examples. The process integrates unmanned aerial vehicles (UAVs) also commonly known as drones, high-resolution red, green, blue colour model (RGB) cameras, and a data processing approach based on machine learning algorithms. The methods are illustrated with data acquired in Cape Range National Park, Western Australia (WA), Australia, orthorectified in Agisoft Photoscan Pro, and processed in Python programming language, scikit-learn, and eXtreme Gradient Boosting (XGBoost) libraries. In total, 342,626 samples were extracted from the obtained data set and labelled into six classes. Segmentation results provided an individual detection rate of 97% for buffel grass and 96% for spinifex, with a global multiclass pixel-wise detection rate of 97%. Obtained results were robust against illumination changes, object rotation, occlusion, background cluttering, and floral density variation. PMID:29462912

Top-down and bottom-up aerosol-cloud closure: towards understanding sources of uncertainty in deriving cloud shortwave radiative flux

NASA Astrophysics Data System (ADS)

Sanchez, Kevin J.; Roberts, Gregory C.; Calmer, Radiance; Nicoll, Keri; Hashimshoni, Eyal; Rosenfeld, Daniel; Ovadnevaite, Jurgita; Preissler, Jana; Ceburnis, Darius; O'Dowd, Colin; Russell, Lynn M.

2017-08-01

Top-down and bottom-up aerosol-cloud shortwave radiative flux closures were conducted at the Mace Head Atmospheric Research Station in Galway, Ireland, in August 2015. This study is part of the BACCHUS (Impact of Biogenic versus Anthropogenic emissions on Clouds and Climate: towards a Holistic UnderStanding) European collaborative project, with the goal of understanding key processes affecting aerosol-cloud shortwave radiative flux closures to improve future climate predictions and develop sustainable policies for Europe. Instrument platforms include ground-based unmanned aerial vehicles (UAVs)1 and satellite measurements of aerosols, clouds and meteorological variables. The ground-based and airborne measurements of aerosol size distributions and cloud condensation nuclei (CCN) concentration were used to initiate a 1-D microphysical aerosol-cloud parcel model (ACPM). UAVs were equipped for a specific science mission, with an optical particle counter for aerosol distribution profiles, a cloud sensor to measure cloud extinction or a five-hole probe for 3-D wind vectors. UAV cloud measurements are rare and have only become possible in recent years through the miniaturization of instrumentation. These are the first UAV measurements at Mace Head. ACPM simulations are compared to in situ cloud extinction measurements from UAVs to quantify closure in terms of cloud shortwave radiative flux. Two out of seven cases exhibit sub-adiabatic vertical temperature profiles within the cloud, which suggests that entrainment processes affect cloud microphysical properties and lead to an overestimate of simulated cloud shortwave radiative flux. Including an entrainment parameterization and explicitly calculating the entrainment fraction in the ACPM simulations both improved cloud-top radiative closure. Entrainment reduced the difference between simulated and observation-derived cloud-top shortwave radiative flux (δRF) by between 25 and 60 W m-2. After accounting for entrainment, satellite-derived cloud droplet number concentrations (CDNCs) were within 30 % of simulated CDNC. In cases with a well-mixed boundary layer, δRF is no greater than 20 W m-2 after accounting for cloud-top entrainment and up to 50 W m-2 when entrainment is not taken into account. In cases with a decoupled boundary layer, cloud microphysical properties are inconsistent with ground-based aerosol measurements, as expected, and δRF is as high as 88 W m-2, even high (> 30 W m-2) after accounting for cloud-top entrainment. This work demonstrates the need to take in situ measurements of aerosol properties for cases where the boundary layer is decoupled as well as consider cloud-top entrainment to accurately model stratocumulus cloud radiative flux. 1The regulatory term for UAV is remotely piloted aircraft (RPA).

Urban forest topographical mapping using UAV LIDAR

NASA Astrophysics Data System (ADS)

Putut Ash Shidiq, Iqbal; Wibowo, Adi; Kusratmoko, Eko; Indratmoko, Satria; Ardhianto, Ronni; Prasetyo Nugroho, Budi

2017-12-01

Topographical data is highly needed by many parties, such as government institution, mining companies and agricultural sectors. It is not just about the precision, the acquisition time and data processing are also carefully considered. In relation with forest management, a high accuracy topographic map is necessary for planning, close monitoring and evaluating forest changes. One of the solution to quickly and precisely mapped topography is using remote sensing system. In this study, we test high-resolution data using Light Detection and Ranging (LiDAR) collected from unmanned aerial vehicles (UAV) to map topography and differentiate vegetation classes based on height in urban forest area of University of Indonesia (UI). The semi-automatic and manual classifications were applied to divide point clouds into two main classes, namely ground and vegetation. There were 15,806,380 point clouds obtained during the post-process, in which 2.39% of it were detected as ground.

A mathematical analysis of the Janus combat simulation weather effects models and sensitivity analysis of sky-to-ground brightness ratio on target detection

NASA Astrophysics Data System (ADS)

Shorts, Vincient F.

1994-09-01

The Janus combat simulation offers the user a wide variety of weather effects options to employ during the execution of any simulation run, which can directly influence detection of opposing forces. Realistic weather effects are required if the simulation is to accurately reproduce 'real world' results. This thesis examines the mathematics of the Janus weather effects models. A weather effect option in Janus is the sky-to-ground brightness ratio (SGR). SGR affects an optical sensor's ability to detect targets. It is a measure of the sun angle in relation to the horizon. A review of the derivation of SGR is performed and an analysis of SGR's affect on the number of optical detections and detection ranges is performed using an unmanned aerial vehicle (UAV) search scenario. For comparison, the UAV's are equipped with a combination of optical and thermal sensors.

Surveillance of ground vehicles for airport security

NASA Astrophysics Data System (ADS)

Blasch, Erik; Wang, Zhonghai; Shen, Dan; Ling, Haibin; Chen, Genshe

2014-06-01

Future surveillance systems will work in complex and cluttered environments which require systems engineering solutions for such applications such as airport ground surface management. In this paper, we highlight the use of a L1 video tracker for monitoring activities at an airport. We present methods of information fusion, entity detection, and activity analysis using airport videos for runway detection and airport terminal events. For coordinated airport security, automated ground surveillance enhances efficient and safe maneuvers for aircraft, unmanned air vehicles (UAVs) and unmanned ground vehicles (UGVs) operating within airport environments.

Nearshore Measurements From a Small UAV.

NASA Astrophysics Data System (ADS)

Holman, R. A.; Brodie, K. L.; Spore, N.

2016-02-01

Traditional measurements of nearshore hydrodynamics and evolving bathymetry are expensive and dangerous and must be frequently repeated to track the rapid changes of typical ocean beaches. However, extensive research into remote sensing methods using cameras or radars mounted on fixed towers has resulted in increasingly mature algorithms for estimating bathymetry, currents and wave characteristics. This naturally raises questions about how easily and effectively these algorithms can be applied to optical data from low-cost, easily-available UAV platforms. This paper will address the characteristics and quality of data taken from a small, low-cost UAV, the DJI Phantom. In particular, we will study the stability of imagery from a vehicle `parked' at 300 feet altitude, methods to stabilize remaining wander, and the quality of nearshore bathymetry estimates from the resulting image time series, computed using the cBathy algorithm. Estimates will be compared to ground truth surveys collected at the Field Research Facility at Duck, NC.

Bringing UAVs to the fight: recent army autonomy research and a vision for the future

NASA Astrophysics Data System (ADS)

Moorthy, Jay; Higgins, Raymond; Arthur, Keith

2008-04-01

The Unmanned Autonomous Collaborative Operations (UACO) program was initiated in recognition of the high operational burden associated with utilizing unmanned systems by both mounted and dismounted, ground and airborne warfighters. The program was previously introduced at the 62nd Annual Forum of the American Helicopter Society in May of 20061. This paper presents the three technical approaches taken and results obtained in UACO. All three approaches were validated extensively in contractor simulations, two were validated in government simulation, one was flight tested outside the UACO program, and one was flight tested in Part 2 of UACO. Results and recommendations are discussed regarding diverse areas such as user training and human-machine interface, workload distribution, UAV flight safety, data link bandwidth, user interface constructs, adaptive algorithms, air vehicle system integration, and target recognition. Finally, a vision for UAV As A Wingman is presented.

Embedded, real-time UAV control for improved, image-based 3D scene reconstruction

Treesearch

Jean Liénard; Andre Vogs; Demetrios Gatziolis; Nikolay Strigul

2016-01-01

Unmanned Aerial Vehicles (UAVs) are already broadly employed for 3D modeling of large objects such as trees and monuments via photogrammetry. The usual workflow includes two distinct steps: image acquisition with UAV and computationally demanding postflight image processing. Insufficient feature overlaps across images is a common shortcoming in post-flight image...

Enabling efficient vertical takeoff/landing and forward flight of unmanned aerial vehicles: Design and control of tandem wing-tip mounted rotor mechanisms

NASA Astrophysics Data System (ADS)

Mancuso, Peter Timothy

Fixed-wing unmanned aerial vehicles (UAVs) that offer vertical takeoff and landing (VTOL) and forward flight capability suffer from sub-par performance in both flight modes. Achieving the next generation of efficient hybrid aircraft requires innovations in: (i) power management, (ii) efficient structures, and (iii) control methodologies. Existing hybrid UAVs generally utilize one of three transitioning mechanisms: an external power mechanism to tilt the rotor-propulsion pod, separate propulsion units and rotors during hover and forward flight, or tilt body craft (smaller scale). Thus, hybrid concepts require more energy compared to dedicated fixed-wing or rotorcraft UAVs. Moreover, design trade-offs to reinforce the wing structure (typically to accommodate the propulsion systems and enable hover, i.e. tilt-rotor concepts) adversely impacts the aerodynamics, controllability and efficiency of the aircraft in both hover and forward flight modes. The goal of this research is to develop more efficient VTOL/ hover and forward flight UAVs. In doing so, the transition sequence, transition mechanism, and actuator performance are heavily considered. A design and control methodology was implemented to address these issues through a series of computer simulations and prototype benchtop tests to verify the proposed solution. Finally, preliminary field testing with a first-generation prototype was conducted. The methods used in this research offer guidelines and a new dual-arm rotor UAV concept to designing more efficient hybrid UAVs in both hover and forward flight.

UAV-Based Thermal Imaging for High-Throughput Field Phenotyping of Black Poplar Response to Drought

PubMed Central

Ludovisi, Riccardo; Tauro, Flavia; Salvati, Riccardo; Khoury, Sacha; Mugnozza Scarascia, Giuseppe; Harfouche, Antoine

2017-01-01

Poplars are fast-growing, high-yielding forest tree species, whose cultivation as second-generation biofuel crops is of increasing interest and can efficiently meet emission reduction goals. Yet, breeding elite poplar trees for drought resistance remains a major challenge. Worldwide breeding programs are largely focused on intra/interspecific hybridization, whereby Populus nigra L. is a fundamental parental pool. While high-throughput genotyping has resulted in unprecedented capabilities to rapidly decode complex genetic architecture of plant stress resistance, linking genomics to phenomics is hindered by technically challenging phenotyping. Relying on unmanned aerial vehicle (UAV)-based remote sensing and imaging techniques, high-throughput field phenotyping (HTFP) aims at enabling highly precise and efficient, non-destructive screening of genotype performance in large populations. To efficiently support forest-tree breeding programs, ground-truthing observations should be complemented with standardized HTFP. In this study, we develop a high-resolution (leaf level) HTFP approach to investigate the response to drought of a full-sib F2 partially inbred population (termed here ‘POP6’), whose F1 was obtained from an intraspecific P. nigra controlled cross between genotypes with highly divergent phenotypes. We assessed the effects of two water treatments (well-watered and moderate drought) on a population of 4603 trees (503 genotypes) hosted in two adjacent experimental plots (1.67 ha) by conducting low-elevation (25 m) flights with an aerial drone and capturing 7836 thermal infrared (TIR) images. TIR images were undistorted, georeferenced, and orthorectified to obtain radiometric mosaics. Canopy temperature (Tc) was extracted using two independent semi-automated segmentation techniques, eCognition- and Matlab-based, to avoid the mixed-pixel problem. Overall, results showed that the UAV platform-based thermal imaging enables to effectively assess genotype variability under drought stress conditions. Tc derived from aerial thermal imagery presented a good correlation with ground-truth stomatal conductance (gs) in both segmentation techniques. Interestingly, the HTFP approach was instrumental to detect drought-tolerant response in 25% of the population. This study shows the potential of UAV-based thermal imaging for field phenomics of poplar and other tree species. This is anticipated to have tremendous implications for accelerating forest tree genetic improvement against abiotic stress. PMID:29021803

Mapping surface temperature variability on a debris-covered glacier with an unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Kraaijenbrink, P. D. A.; Litt, M.; Shea, J. M.; Treichler, D.; Koch, I.; Immerzeel, W.

2016-12-01

Debris-covered glacier tongues cover about 12% of the glacier surface in high mountain Asia and much of the melt water is generated from those glaciers. A thin layer of supraglacial debris enhances ice melt by lowering the albedo, while thicker debris insulates the ice and reduces melt. Data on debris thickness is therefore an important input for energy balance modelling of these glaciers. Thermal infrared remote sensing can be used to estimate the debris thickness by using an inverse relation between debris surface temperature and thickness. To date this has only been performed using coarse spaceborne thermal imagery, which cannot reveal small scale variation in debris thickness and its influence on the heterogeneous melt patterns on debris-covered glaciers. We deployed an unmanned aerial vehicle mounted with a thermal infrared sensor over the debris-covered Lirung Glacier in Nepal three times in May 2016 to reveal the spatial and temporal variability of surface temperature in high detail. The UAV survey matched a Landsat 8 overpass to be able to make a comparison with spaceborne thermal imagery. The UAV-acquired data is processed using Structure from Motion photogrammetry and georeferenced using DGPS-measured ground control points. Different surface types were distinguished by using data acquired by an additional optical UAV survey in order to correct for differences in surface emissivity. In situ temperature measurements and incoming solar radiation data are used to calibrate the temperature calculations. Debris thicknesses derived are validated by thickness measurements of a ground penetrating radar. Preliminary analysis reveals a spatially highly heterogeneous pattern of surface temperature over Lirung Glacier with a range in temperature of over 40 K. At dawn the debris is relatively cold and its temperature is influenced strongly by the ice underneath. Exposed to the high solar radiation at the high altitude the debris layer heats up very rapidly as sunrise progresses, and the influence of ice on debris surface temperature reduces considerably. Many patterns are revealed that cannot be detected from the Landsat data, both on small spatial and temporal scales. The high detail the UAV-borne thermal imagery provides in time and space has great potential in the research of debris cover and its characteristics.

UAV-Based Thermal Imaging for High-Throughput Field Phenotyping of Black Poplar Response to Drought.

PubMed

Ludovisi, Riccardo; Tauro, Flavia; Salvati, Riccardo; Khoury, Sacha; Mugnozza Scarascia, Giuseppe; Harfouche, Antoine

2017-01-01

Poplars are fast-growing, high-yielding forest tree species, whose cultivation as second-generation biofuel crops is of increasing interest and can efficiently meet emission reduction goals. Yet, breeding elite poplar trees for drought resistance remains a major challenge. Worldwide breeding programs are largely focused on intra/interspecific hybridization, whereby Populus nigra L. is a fundamental parental pool. While high-throughput genotyping has resulted in unprecedented capabilities to rapidly decode complex genetic architecture of plant stress resistance, linking genomics to phenomics is hindered by technically challenging phenotyping. Relying on unmanned aerial vehicle (UAV)-based remote sensing and imaging techniques, high-throughput field phenotyping (HTFP) aims at enabling highly precise and efficient, non-destructive screening of genotype performance in large populations. To efficiently support forest-tree breeding programs, ground-truthing observations should be complemented with standardized HTFP. In this study, we develop a high-resolution (leaf level) HTFP approach to investigate the response to drought of a full-sib F 2 partially inbred population (termed here 'POP6'), whose F 1 was obtained from an intraspecific P. nigra controlled cross between genotypes with highly divergent phenotypes. We assessed the effects of two water treatments (well-watered and moderate drought) on a population of 4603 trees (503 genotypes) hosted in two adjacent experimental plots (1.67 ha) by conducting low-elevation (25 m) flights with an aerial drone and capturing 7836 thermal infrared (TIR) images. TIR images were undistorted, georeferenced, and orthorectified to obtain radiometric mosaics. Canopy temperature ( T c ) was extracted using two independent semi-automated segmentation techniques, eCognition- and Matlab-based, to avoid the mixed-pixel problem. Overall, results showed that the UAV platform-based thermal imaging enables to effectively assess genotype variability under drought stress conditions. T c derived from aerial thermal imagery presented a good correlation with ground-truth stomatal conductance ( g s ) in both segmentation techniques. Interestingly, the HTFP approach was instrumental to detect drought-tolerant response in 25% of the population. This study shows the potential of UAV-based thermal imaging for field phenomics of poplar and other tree species. This is anticipated to have tremendous implications for accelerating forest tree genetic improvement against abiotic stress.

UAV and SfM in Detailed Geomorphological Mapping of Granite Tors: An Example of Starościńskie Skały (Sudetes, SW Poland)

NASA Astrophysics Data System (ADS)

Kasprzak, Marek; Jancewicz, Kacper; Michniewicz, Aleksandra

2017-11-01

The paper presents an example of using photographs taken by unmanned aerial vehicles (UAV) and processed using the structure from motion (SfM) procedure in a geomorphological study of rock relief. Subject to analysis is a small rock city in the West Sudetes (SW Poland), known as Starościńskie Skały and developed in coarse granite bedrock. The aims of this paper were, first, to compare UAV/SfM-derived data with the cartographical image based on the traditional geomorphological field-mapping methods and the digital elevation model derived from airborne laser scanning (ALS). Second, to test if the proposed combination of UAV and SfM methods may be helpful in recognizing the detailed structure of granite tors. As a result of conducted UAV flights and digital image post-processing in AgiSoft software, it was possible to obtain datasets (dense point cloud, texture model, orthophotomap, bare-ground-type digital terrain model—DTM) which allowed to visualize in detail the surface of the study area. In consequence, it was possible to distinguish even the very small forms of rock surface microrelief: joints, aplite veins, rills and karren, weathering pits, etc., otherwise difficult to map and measure. The study includes also valorization of particular datasets concerning microtopography and allows to discuss indisputable advantages of using the UAV/SfM-based DTM in geomorphic studies of tors and rock cities, even those located within forest as in the presented case study.

Managing the integration and harmonization of national airspace for unmanned and manned systems

NASA Astrophysics Data System (ADS)

Mumm, Hans

This dissertation examines the leadership challenge created by the requirement to integrate unmanned aerial vehicles (UAVs) into the national airspace system (NAS). The lack of UAV-related federal rules and regulations is a primary factor prolonging this integration. This effort focuses primarily on the leadership portion of the solution and not the technological requirements. The research explores an adaptation of the complexity theory that offers a potential leadership framework for the government, industry, and academia to use for achieving the full integration of UAVs into the NAS. Due to the large number of stakeholders and the multitude of interrelated issues, a complexity-theory-leadership methodology was created and examined as a potential way to help the FAA accelerate their rule-making efforts. This dissertation focuses on United States UAV issues. The United States is one of the leaders in the unmanned systems arena, to include the first significant use of recoverable autonomous weaponized systems in combat. Issues such as airspace, airworthiness, social issues, privacy issues, regulations, and the lack of policies, procedures, or governance are universal for all countries that are active in this technology area. This qualitative dissertation makes use of the grounded theory methodology as it combines a literature review and research along with interviews with subject matter experts, and information gained from attending UAV related gatherings/discussions. The investigation uncovered significant FAA process impediments as well as some possible break through concepts that could work well with the complexity-theory-leadership methodology. Keywords: Complexity theory, leadership, change management, UAV, unmanned aerial vehicle, National Airspace, NAS, FAA, Federal Aviation Administration.

Distributed Actuation and Sensing on an Uninhabited Aerial Vehicle

NASA Technical Reports Server (NTRS)

Barnwell, William Garrard

2003-01-01

An array of effectors and sensors has been designed, tested and implemented on a Blended Wing Body Uninhabited Aerial Vehicle (UAV). The UAV is modified to serve as a flying, controls research, testbed. This effector/sensor array provides for the dynamic vehicle testing of controller designs and the study of decentralized control techniques. Each wing of the UAV is equipped with 12 distributed effectors that comprise a segmented array of independently actuated, contoured control surfaces. A single pressure sensor is installed near the base of each effector to provide a measure of deflections of the effectors. The UAV wings were tested in the North Carolina State University Subsonic Wind Tunnel and the pressure distribution that result from the deflections of the effectors are characterized. The results of the experiments are used to develop a simple, but accurate, prediction method, such that for any arrangement of the effector array the corresponding pressure distribution can be determined. Numerical analysis using the panel code CMARC verifies this prediction method.

Using Unmanned Aerial Vehicles (UAVs) to Modeling Tornado Impacts

NASA Astrophysics Data System (ADS)

Wagner, M.; Doe, R. K.

2017-12-01

Using Unmanned Aerial Vehicles (UAVs) to assess storm damage is a useful research tool. Benefits include their ability to access remote or impassable areas post-storm, identify unknown damages and assist with more detailed site investigations and rescue efforts. Technological advancement of UAVs mean that they can capture high resolution images often at an affordable price. These images can be used to create 3D environments to better interpret and delineate damages from large areas that would have been difficult in ground surveys. This research presents the results of a rapid response site investigation of the 29 April 2017 Canton, Texas, USA, tornado using low cost UAVs. This was a multiple, high impact tornado event measuring EF4 at maximum. Rural farmland was chosen as a challenging location to test both equipment and methodology. Such locations provide multiple impacts at a variety of scales including structural and vegetation damage and even animal fatalities. The 3D impact models allow for a more comprehensive study prior to clean-up. The results show previously unseen damages and better quantify damage impacts at the local level. 3D digital track swaths were created allowing for a more accurate track width determination. These results demonstrate how effective the use of low cost UAVs can be for rapid response storm damage assessments, the high quality of data they can achieve, and how they can help us better visualize tornado site investigations.

Derivation of high spatial resolution albedo from UAV digital imagery: application over the Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

Ryan, Jonathan C.; Hubbard, Alun; Box, Jason E.; Brough, Stephen; Cameron, Karen; Cook, Joseph M.; Cooper, Matthew; Doyle, Samuel H.; Edwards, Arwyn; Holt, Tom; Irvine-Fynn, Tristram; Jones, Christine; Pitcher, Lincoln H.; Rennermalm, Asa K.; Smith, Laurence C.; Stibal, Marek; Snooke, Neal

2017-05-01

Measurements of albedo are a prerequisite for modelling surface melt across the Earth's cryosphere, yet available satellite products are limited in spatial and/or temporal resolution. Here, we present a practical methodology to obtain centimetre resolution albedo products with accuracies of 5% using consumer-grade digital camera and unmanned aerial vehicle (UAV) technologies. Our method comprises a workflow for processing, correcting and calibrating raw digital images using a white reference target, and upward and downward shortwave radiation measurements from broadband silicon pyranometers. We demonstrate the method with a set of UAV sorties over the western, K-sector of the Greenland Ice Sheet. The resulting albedo product, UAV10A1, covers 280 km2, at a resolution of 20 cm per pixel and has a root-mean-square difference of 3.7% compared to MOD10A1 and 4.9% compared to ground-based broadband pyranometer measurements. By continuously measuring downward solar irradiance, the technique overcomes previous limitations due to variable illumination conditions during and between surveys over glaciated terrain. The current miniaturization of multispectral sensors and incorporation of upward facing radiation sensors on UAV packages means that this technique will likely become increasingly attractive in field studies and used in a wide range of applications for high temporal and spatial resolution surface mapping of debris, dust, cryoconite and bioalbedo and for directly constraining surface energy balance models.

High Resolution UAV-based Passive Microwave L-band Imaging of Soil Moisture

NASA Astrophysics Data System (ADS)

Gasiewski, A. J.; Stachura, M.; Elston, J.; McIntyre, E. M.

2013-12-01

Due to long electrical wavelengths and aperture size limitations the scaling of passive microwave remote sensing of soil moisture from spaceborne low-resolution applications to high resolution applications suitable for precision agriculture requires use of low flying aerial vehicles. This presentation summarizes a project to develop a commercial Unmanned Aerial Vehicle (UAV) hosting a precision microwave radiometer for mapping of soil moisture in high-value shallow root-zone crops. The project is based on the use of the Tempest electric-powered UAV and a compact digital L-band (1400-1427 MHz) passive microwave radiometer developed specifically for extremely small and lightweight aerial platforms or man-portable, tractor, or tower-based applications. Notable in this combination are a highly integrated UAV/radiometer antenna design and use of both the upwelling emitted signal from the surface and downwelling cold space signal for precise calibration using a lobe-correlating radiometer architecture. The system achieves a spatial resolution comparable to the altitude of the UAV above the ground while referencing upwelling measurements to the constant and well-known background temperature of cold space. The radiometer incorporates digital sampling and radio frequency interference mitigation along with infrared, near-infrared, and visible (red) sensors for surface temperature and vegetation biomass correction. This NASA-sponsored project is being developed both for commercial application in cropland water management, L-band satellite validation, and estuarian plume studies.

Development of an Effective System Identification and Control Capability for Quad-copter UAVs

NASA Astrophysics Data System (ADS)

Wei, Wei

In recent years, with the promise of extensive commercial applications, the popularity of Unmanned Aerial Vehicles (UAVs) has dramatically increased as witnessed by publications and mushrooming research and educational programs. Over the years, multi-copter aircraft have been chosen as a viable configuration for small-scale VTOL UAVs in the form of quad-copters, hexa-copters and octo-copters. Compared to the single main rotor configuration such as the conventional helicopter, multi-copter airframes require a simpler feedback control system and fewer mechanical parts. These characteristics make these UAV platforms, such as quad-copter which is the main emphasis in this dissertation, a rugged and competitive candidate for many applications in both military and civil areas. Because of its configuration and relative size, the small-scale quad-copter UAV system is inherently very unstable. In order to develop an effective control system through simulation techniques, obtaining an accurate dynamic model of a given quad-copter is imperative. Moreover, given the anticipated stringent safety requirements, fault tolerance will be a crucial component of UAV certification. Accurate dynamic modeling and control of this class of UAV is an enabling technology and is imperative for future commercial applications. In this work, the dynamic model of a quad-copter system in hover flight was identified using frequency-domain system identification techniques. A new and unique experimental system, data acquisition and processing procedure was developed catering specifically to the class of electric powered multi-copter UAV systems. The Comprehensive Identification from FrEquency Responses (CIFER RTM) software package, developed by US Army Aviation Development Directorate -- AFDD, was utilized along with flight tests to develop dynamic models of the quad-copter system. A new set of flight tests were conducted and the predictive capability of the dynamic models were successfully validated. A PID controller and two fuzzy logic controllers were developed based on the validated dynamic models. The controller performances were evaluated and compared in both simulation environment and flight testing. Flight controllers were optimized to comply with US Aeronautical Design Standard Performance Specification Handling Quality Requirements for Military Rotorcraft (ADS-33E-PRF). Results showed a substantial improvement for developed controllers when compared to the nominal controllers based on hand tuning. The scope of this research involves experimental system hardware and software development, flight instrumentation, flight testing, dynamics modeling, system identification, dynamic model validation, control system modeling using PID and fuzzy logic, analysis of handling qualities, flight control optimization and validation. Both closed-loop and open-loop dynamics of the quad-copter system were analyzed. A cost-effective and high quality system identification procedure was applied and results proved in simulations as well as in flight tests.

A Q-Learning Approach to Flocking With UAVs in a Stochastic Environment.

PubMed

Hung, Shao-Ming; Givigi, Sidney N

2017-01-01

In the past two decades, unmanned aerial vehicles (UAVs) have demonstrated their efficacy in supporting both military and civilian applications, where tasks can be dull, dirty, dangerous, or simply too costly with conventional methods. Many of the applications contain tasks that can be executed in parallel, hence the natural progression is to deploy multiple UAVs working together as a force multiplier. However, to do so requires autonomous coordination among the UAVs, similar to swarming behaviors seen in animals and insects. This paper looks at flocking with small fixed-wing UAVs in the context of a model-free reinforcement learning problem. In particular, Peng's Q(λ) with a variable learning rate is employed by the followers to learn a control policy that facilitates flocking in a leader-follower topology. The problem is structured as a Markov decision process, where the agents are modeled as small fixed-wing UAVs that experience stochasticity due to disturbances such as winds and control noises, as well as weight and balance issues. Learned policies are compared to ones solved using stochastic optimal control (i.e., dynamic programming) by evaluating the average cost incurred during flight according to a cost function. Simulation results demonstrate the feasibility of the proposed learning approach at enabling agents to learn how to flock in a leader-follower topology, while operating in a nonstationary stochastic environment.

Towards FAA Certification of UAVs

NASA Technical Reports Server (NTRS)

Nelson, Stacy

2003-01-01

As of June 30, 2003, all Unmanned Aerial Vehicles (UAV), no matter how small, must adhere to the same FAA regulations as human-piloted aircraft. These regulations include certification for flying in controlled airspace and certification of flight software based on RTCA DO-178B. This paper provides an overview of the steps necessary to obtain certification, as well as a discussion about the challenges UAV's face when trying to meet these requirements. It is divided into two parts: 1) Certifications for Flying in Controlled Airspace; 2) Certification of Flight Software per RTCA DO-178B.

Use of the RoboFlag synthetic task environment to investigate workload and stress responses in UAV operation.

PubMed

Guznov, Svyatoslav; Matthews, Gerald; Funke, Gregory; Dukes, Allen

2011-09-01

Use of unmanned aerial vehicles (UAVs) is an increasingly important element of military missions. However, controlling UAVs may impose high stress and workload on the operator. This study evaluated the use of the RoboFlag simulated environment as a means for profiling multiple dimensions of stress and workload response to a task requiring control of multiple vehicles (robots). It tested the effects of two workload manipulations, environmental uncertainty (i.e., UAV's visual view area) and maneuverability, in 64 participants. The findings confirmed that the task produced substantial workload and elevated distress. Dissociations between the stress and performance effects of the manipulations confirmed the utility of a multivariate approach to assessment. Contrary to expectations, distress and some aspects of workload were highest in the low-uncertainty condition, suggesting that overload of information may be an issue for UAV interface designers. The strengths and limitations of RoboFlag as a methodology for investigating stress and workload responses are discussed.

Development of Hardware-in-the-Loop Simulation Based on Gazebo and Pixhawk for Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Nguyen, Khoa Dang; Ha, Cheolkeun

2018-04-01

Hardware-in-the-loop simulation (HILS) is well known as an effective approach in the design of unmanned aerial vehicles (UAV) systems, enabling engineers to test the control algorithm on a hardware board with a UAV model on the software. Performance of HILS is determined by performances of the control algorithm, the developed model, and the signal transfer between the hardware and software. The result of HILS is degraded if any signal could not be transferred to the correct destination. Therefore, this paper aims to develop a middleware software to secure communications in HILS system for testing the operation of a quad-rotor UAV. In our HILS, the Gazebo software is used to generate a nonlinear six-degrees-of-freedom (6DOF) model, sensor model, and 3D visualization for the quad-rotor UAV. Meanwhile, the flight control algorithm is designed and implemented on the Pixhawk hardware. New middleware software, referred to as the control application software (CAS), is proposed to ensure the connection and data transfer between Gazebo and Pixhawk using the multithread structure in Qt Creator. The CAS provides a graphical user interface (GUI), allowing the user to monitor the status of packet transfer, and perform the flight control commands and the real-time tuning parameters for the quad-rotor UAV. Numerical implementations have been performed to prove the effectiveness of the middleware software CAS suggested in this paper.

Tools for DIY site-testing

NASA Astrophysics Data System (ADS)

Flores, Federico; Rondanelli, Roberto; Abarca, Accel; Diaz, Marcos; Querel, Richard

2012-09-01

Our group has designed, sourced and constructed a radiosonde/ground-station pair using inexpensive opensource hardware. Based on the Arduino platform, the easy to build radiosonde allows the atmospheric science community to test and deploy instrumentation packages that can be fully customized to their individual sensing requirements. This sensing/transmitter package has been successfully deployed on a tethered-balloon, a weather balloon, a UAV airplane, and is currently being integrated into a UAV quadcopter and a student-built rocket. In this paper, the system, field measurements and potential applications will be described. As will the science drivers of having full control and open access to a measurement system in an age when commercial solutions have become popular but are restrictive in terms of proprietary sensor specifications, "black-box" calibration operations or data handling routines, etc. The ability to modify and experiment with both the hardware and software tools is an essential part of the scientific process. Without an understanding of the intrinsic biases or limitations in your instruments and system, it becomes difficult to improve them or advance the knowledge in any given field.

EM Modeling of Far-Field Radiation Patterns for Antennas on the GMA-TT UAV

NASA Technical Reports Server (NTRS)

Mackenzie, Anne I.

2015-01-01

To optimize communication with the Generic Modular Aircraft T-Tail (GMA-TT) unmanned aerial vehicle (UAV), electromagnetic (EM) simulations have been performed to predict the performance of two antenna types on the aircraft. Simulated far-field radiation patterns tell the amount of power radiated by the antennas and the aircraft together, taking into account blockage by the aircraft as well as radiation by conducting and dielectric portions of the aircraft. With a knowledge of the polarization and distance of the two communicating antennas, e.g. one on the UAV and one on the ground, and the transmitted signal strength, a calculation may be performed to find the strength of the signal travelling from one antenna to the other and to check that the transmitted signal meets the receiver system requirements for the designated range. In order to do this, the antenna frequency and polarization must be known for each antenna, in addition to its design and location. The permittivity, permeability, and geometry of the UAV components must also be known. The full-wave method of moments solution produces the appropriate dBi radiation pattern in which the received signal strength is calculated relative to that of an isotropic radiator.

Geomorphological mapping of shallow landslides using UAVs

NASA Astrophysics Data System (ADS)

Fiorucci, Federica; Giordan, Daniele; Dutto, Furio; Rossi, Mauro; Guzzetti, Fausto

2015-04-01

The mapping of event shallow landslides is a critical activity, due to the large number of phenomena, mostly with small dimension, affecting extensive areas. This is commonly done through aerial photo-interpretation or through field surveys. Nowadays, landslide maps can be realized exploiting other methods/technologies: (i) airborne LiDARs, (ii) stereoscopic satellite images, and (iii) unmanned aerial vehicles (UAVs). In addition to the landslide maps, these methods/technologies allow the generation of updated Digital Terrain Models (DTM). In December 2013, in the Collazzone area (Umbria, Central Italy), an intense rainfall event triggered a large number of shallow landslides. To map the landslides occurred in the area, we exploited data and images obtained through (A) an airborne LiDAR survey, (B) a remote controlled optocopter (equipped with a Canon EOS M) survey, and (C) a stereoscopic satellite WorldView II MS. To evaluate the mapping accuracy of these methods, we select two landslides and we mapped them using a GPS RTK instrumentation. We consider the GPS survey as the benchmark being the most accurate system. The results of the comparison allow to highlight pros and cons of the methods/technologies used. LiDAR can be considered the most accurate system and in addition it allows the extraction and the classification of the digital surface models from the surveyed point cloud. Conversely, LiDAR requires additional time for the flight planning, and specific data analysis user capabilities. The analysis of the satellite WorldView II MS images facilitates the landslide mapping over large areas, but at the expenses of a minor resolution to detect the smaller landslides and their boundaries. UAVs can be considered the cheapest and fastest solution for the acquisition of high resolution ortho-photographs on limited areas, and the best solution for a multi-temporal analysis of specific landslide phenomena. Limitations are due to (i) the needs of optimal climatic conditions during the acquisition, (ii) the needs of ground control points to be acquired simultaneously with the UAV surveys, and (iii) the restrictive laws existing in different countries that could limit the use of these systems.

Fault-Tolerant and Reconfigurable Control of Unmanned Aerial Vehicles (UAVs)

DTIC Science & Technology

2008-02-29

forces and moments are expressed as functions of angle of attack, sideslip angle, angular rates, and control surface deflection. L, M, and N are...invertible. As for matrix B, the control surfaces of the reusable launch vehicle are designed to control each axes angular rate of aircraft...literature as being invertible. As for matrix B, the control surfaces of the UAV are designed to control angular rate along each axis of the aircraft

Stability analysis of chalk sea cliffs using UAV photogrammetry

NASA Astrophysics Data System (ADS)

Barlow, John; Gilham, Jamie

2017-04-01

Cliff erosion and instability poses a significant hazard to communities and infrastructure located is coastal areas. We use point cloud and spectral data derived from close range digital photogrammetry to assess the stability of chalk sea cliffs located at Telscombe, UK. Data captured from an unmanned aerial vehicle (UAV) were used to generate dense point clouds for a 712 m section of cliff face which ranges from 20 to 49 m in height. Generated models fitted our ground control network within a standard error of 0.03 m. Structural features such as joints, bedding planes, and faults were manually mapped and are consistent with results from other studies that have been conducted using direct measurement in the field. Kinematic analysis of these data was used to identify the primary modes of failure at the site. Our results indicate that wedge failure is by far the most likely mode of slope instability. An analysis of sequential surveys taken from the summer of 2016 to the winter of 2017 indicate several large failures have occurred at the site. We establish the volume of failure through change detection between sequential data sets and use back analysis to determine the strength of shear surfaces for each failure. Our results show that data capture through UAV photogrammetry can provide useful information for slope stability analysis over long sections of cliff. The use of this technology offers significant benefits in equipment costs and field time over existing methods.

Development of a Micro-UAV Hyperspectral Imaging Platform for Assessing Hydrogeological Hazards

NASA Astrophysics Data System (ADS)

Chen, Z.; Alabsi, M.

2015-12-01

The exacerbating global weather changes have cast significant impacts upon the proportion of water supplied to agriculture. Therefore, one of the 21stCentury Grant Challenges faced by global population is securing water for food. However, the soil-water behavior in an agricultural environment is complex; among others, one of the key properties we recognize is water repellence or hydrophobicity, which affects many hydrogeological and hazardous conditions such as excessive water infiltration, runoff, and soil erosion. Under a US-Israel research program funded by USDA and BARD at Israel, we have proposed the development of a novel micro-unmanned aerial vehicle (micro-UAV or drone) based hyperspectral imaging platform for identifying and assessing soil repellence at low altitudes with enhanced flexibility, much reduced cost, and ultimately easy use. This aerial imaging system consists of a generic micro-UAV, hyperspectral sensor aided by GPS/IMU, on-board computing units, and a ground station. The target benefits of this system include: (1) programmable waypoint navigation and robotic control for multi-view imaging; (2) ability of two- or three-dimensional scene reconstruction for complex terrains; and (3) fusion with other sensors to realize real-time diagnosis (e.g., humidity and solar irradiation that may affect soil-water sensing). In this talk we present our methodology and processes in integration of hyperspectral imaging, on-board sensing and computing, hyperspectral data modeling, and preliminary field demonstration and verification of the developed prototype.

Impact of Prior Flight Experience on Learning Predator UAV Operator Skills

DTIC Science & Technology

2002-02-01

UAVs are becoming a mainstay of intelligence , surveillance, and reconnaissance (ISR) information gathering, with the capability of supplying, in...indicators of UAV pilot skill, namely frequency and type of videogame playing, and experience with remote-controlled hobby aircraft. Experience with...indicator, artificial horizon, heading rate indicator, and engine revolutions per minute. The right monitor displays other useful information, such as a

Top-down and Bottom-up aerosol-cloud-closure: towards understanding sources of unvertainty in deriving cloud radiative flux

NASA Astrophysics Data System (ADS)

Sanchez, K.; Roberts, G.; Calmer, R.; Nicoll, K.; Hashimshoni, E.; Rosenfeld, D.; Ovadnevaite, J.; Preissler, J.; Ceburnis, D.; O'Dowd, C. D. D.; Russell, L. M.

2017-12-01

Top-down and bottom-up aerosol-cloud shortwave radiative flux closures were conducted at the Mace Head atmospheric research station in Galway, Ireland in August 2015. Instrument platforms include ground-based, unmanned aerial vehicles (UAV), and satellite measurements of aerosols, clouds and meteorological variables. The ground-based and airborne measurements of aerosol size distributions and cloud condensation nuclei (CCN) concentration were used to initiate a 1D microphysical aerosol-cloud parcel model (ACPM). UAVs were equipped for a specific science mission, with an optical particle counter for aerosol distribution profiles, a cloud sensor to measure cloud extinction, or a 5-hole probe for 3D wind vectors. These are the first UAV measurements at Mace Head. ACPM simulations are compared to in-situ cloud extinction measurements from UAVs to quantify closure in terms of cloud shortwave radiative flux. Two out of seven cases exhibit sub-adiabatic vertical temperature profiles within the cloud, which suggests that entrainment processes affect cloud microphysical properties and lead to an overestimate of simulated cloud shortwave radiative flux. Including an entrainment parameterization and explicitly calculating the entrainment fraction in the ACPM simulations both improved cloud-top radiative closure. Entrainment reduced the difference between simulated and observation-derived cloud-top shortwave radiative flux (δRF) by between 25 W m-2 and 60 W m-2. After accounting for entrainment, satellite-derived cloud droplet number concentrations (CDNC) were within 30% of simulated CDNC. In cases with a well-mixed boundary layer, δRF is no greater than 20 W m-2 after accounting for cloud-top entrainment, and up to 50 W m-2 when entrainment is not taken into account. In cases with a decoupled boundary layer, cloud microphysical properties are inconsistent with ground-based aerosol measurements, as expected, and δRF is as high as 88 W m-2, even high (> 30 W m-2) after accounting for cloud-top entrainment. This work demonstrates the need to take in-situ measurements of aerosol properties for cases where the boundary layer is decoupled as well as consider cloud-top entrainment to accurately model stratocumulus cloud radiative flux.

Top-down and Bottom-up aerosol-cloud-closure: towards understanding sources of unvertainty in deriving cloud radiative flux

NASA Astrophysics Data System (ADS)

Sanchez, K.; Roberts, G.; Calmer, R.; Nicoll, K.; Hashimshoni, E.; Rosenfeld, D.; Ovadnevaite, J.; Preissler, J.; Ceburnis, D.; O'Dowd, C. D. D.; Russell, L. M.

2016-12-01

Top-down and bottom-up aerosol-cloud shortwave radiative flux closures were conducted at the Mace Head atmospheric research station in Galway, Ireland in August 2015. Instrument platforms include ground-based, unmanned aerial vehicles (UAV), and satellite measurements of aerosols, clouds and meteorological variables. The ground-based and airborne measurements of aerosol size distributions and cloud condensation nuclei (CCN) concentration were used to initiate a 1D microphysical aerosol-cloud parcel model (ACPM). UAVs were equipped for a specific science mission, with an optical particle counter for aerosol distribution profiles, a cloud sensor to measure cloud extinction, or a 5-hole probe for 3D wind vectors. These are the first UAV measurements at Mace Head. ACPM simulations are compared to in-situ cloud extinction measurements from UAVs to quantify closure in terms of cloud shortwave radiative flux. Two out of seven cases exhibit sub-adiabatic vertical temperature profiles within the cloud, which suggests that entrainment processes affect cloud microphysical properties and lead to an overestimate of simulated cloud shortwave radiative flux. Including an entrainment parameterization and explicitly calculating the entrainment fraction in the ACPM simulations both improved cloud-top radiative closure. Entrainment reduced the difference between simulated and observation-derived cloud-top shortwave radiative flux (δRF) by between 25 W m-2 and 60 W m-2. After accounting for entrainment, satellite-derived cloud droplet number concentrations (CDNC) were within 30% of simulated CDNC. In cases with a well-mixed boundary layer, δRF is no greater than 20 W m-2 after accounting for cloud-top entrainment, and up to 50 W m-2 when entrainment is not taken into account. In cases with a decoupled boundary layer, cloud microphysical properties are inconsistent with ground-based aerosol measurements, as expected, and δRF is as high as 88 W m-2, even high (> 30 W m-2) after accounting for cloud-top entrainment. This work demonstrates the need to take in-situ measurements of aerosol properties for cases where the boundary layer is decoupled as well as consider cloud-top entrainment to accurately model stratocumulus cloud radiative flux.

A distributed automatic target recognition system using multiple low resolution sensors

NASA Astrophysics Data System (ADS)

Yue, Zhanfeng; Lakshmi Narasimha, Pramod; Topiwala, Pankaj

2008-04-01

In this paper, we propose a multi-agent system which uses swarming techniques to perform high accuracy Automatic Target Recognition (ATR) in a distributed manner. The proposed system can co-operatively share the information from low-resolution images of different looks and use this information to perform high accuracy ATR. An advanced, multiple-agent Unmanned Aerial Vehicle (UAV) systems-based approach is proposed which integrates the processing capabilities, combines detection reporting with live video exchange, and swarm behavior modalities that dramatically surpass individual sensor system performance levels. We employ real-time block-based motion analysis and compensation scheme for efficient estimation and correction of camera jitter, global motion of the camera/scene and the effects of atmospheric turbulence. Our optimized Partition Weighted Sum (PWS) approach requires only bitshifts and additions, yet achieves a stunning 16X pixel resolution enhancement, which is moreover parallizable. We develop advanced, adaptive particle-filtering based algorithms to robustly track multiple mobile targets by adaptively changing the appearance model of the selected targets. The collaborative ATR system utilizes the homographies between the sensors induced by the ground plane to overlap the local observation with the received images from other UAVs. The motion of the UAVs distorts estimated homography frame to frame. A robust dynamic homography estimation algorithm is proposed to address this, by using the homography decomposition and the ground plane surface estimation.

Use of Unmanned Aerial Vehicles for Improving Farm Scale Agricultural Water Management in Agriculture at a Farm Scale. A case study for field crops in the California's Central Valley

NASA Astrophysics Data System (ADS)

Medellin-Azuara, J.; Morande, J. A.; Jin, Y.; Chen, Y.; Paw U, K. T.; Viers, J. H.

2016-12-01

Traditional methods for estimating consumptive water use as evapotranspiration (ET) for agriculture in areas with water limitations such as California have always been a challenge for farmers, water managers, researchers and government agencies. Direct measurement of evapotranspiration (ET) and crop water stress in agriculture can be a cumbersome and costly task. Furthermore, spatial variability of applied water and irrigation and stress level in crops, due to inherent heterogeneity in soil conditions, topography, management practices, and lack of uniformity in water applications may affect estimates water use efficiency and water balances. This situation difficult long-term management of agroecosystems. This paper presents a case study for various areas in California's Central Valley using Unmanned Aerial Vehicles (UAVs) for a late portion of the 2016 irrigation season These estimates are compared those obtained by direct measurement (from previously deployed stations), and energy balance approaches with remotely sensed data in a selection of field crop parcels. This research improves information on water use and site conditions in agriculture by enhancing remote sensing-based estimations through the use of higher resolution multi-spectral and thermal imagery captured by UAV. We assess whether more frequent information at higher spatial resolution from UAVs can improve estimations of overall ET through energy balance and imagery. Stress levels and ET are characterized spatially to examine irrigation practices and their performance to improve water use in the agroecosystem. Ground based data such as air and crop temperature and stem water potential is collected to validate UAV aerial measurements. Preliminary results show the potential of UAV technology to improve timing, resolution and accuracy in the ET estimation and assessment of crop stress at a farm scales. Side to side comparison with ground level stations employing surface renewal, eddy covariance and energy balance provides a testbed to improve understanding of consumptive use and crop water management in water scarce irrigated agriculture regions. Keywords. California Central Valley, Agricultural Water Use, Remote Sensing, Energy Balance, Evapotranspiration, Water management,

Guidance and Control of an Autonomous Soaring UAV

NASA Technical Reports Server (NTRS)

Allen, Michael J.; Lin, Victor

2007-01-01

Thermals caused by convection in the lower atmosphere are commonly used by birds and glider pilots to extend flight duration, increase cross-country speed, improve range, or simply to conserve energy. Uninhabited Aerial Vehicles (UAVs) can also increase performance and reduce energy consumption by exploiting atmospheric convection. An autonomous soaring research project was conducted at the NASA Dryden Flight Research Center to evaluate the concept through flight test of an electric-powered motorglider with a wingspan of 4.27 m (14 ft). The UAV's commercial autopilot software was modified to include outer-loop soaring guidance and control. The aircraft total energy state was used to detect and soar within thermals. Estimated thermal size and position were used to calculate guidance commands for soaring flight. Results from a total of 23 thermal encounters show good performance of the guidance and control algorithms to autonomously detect and exploit thermals. The UAV had an average climb of 172 m (567 ft) during these encounters.

Guidance and Control of an Autonomous Soaring UAV

NASA Technical Reports Server (NTRS)

Allen, Michael J.

2007-01-01

Thermals caused by convection in the lower atmosphere are commonly used by birds and glider pilots to extend flight duration, increase cross-country speed, improve range, or simply to conserve energy. Uninhabited Aerial Vehicles (UAVs) can also increase performance and reduce energy consumption by exploiting atmospheric convection. An autonomous soaring research project was conducted at the NASA Dryden Flight Research Center to evaluate the concept through flight test of an electric-powered motor-glider with a wingspan of 4.27 m (14 ft). The UAV's commercial autopilot software was modified to include outer-loop soaring guidance and control. The aircraft total energy state was used to detect and soar within thermals. Estimated thermal size and position were used to calculate guidance commands for soaring flight. Results from a total of 23 thermal encounters show good performance of the guidance and control algorithms to autonomously detect and exploit thermals. The UAV had an average climb of 172 m (567 ft) during these encounters.

Vision and Control for UAVs: A Survey of General Methods and of Inexpensive Platforms for Infrastructure Inspection

PubMed Central

Máthé, Koppány; Buşoniu, Lucian

2015-01-01

Unmanned aerial vehicles (UAVs) have gained significant attention in recent years. Low-cost platforms using inexpensive sensor payloads have been shown to provide satisfactory flight and navigation capabilities. In this report, we survey vision and control methods that can be applied to low-cost UAVs, and we list some popular inexpensive platforms and application fields where they are useful. We also highlight the sensor suites used where this information is available. We overview, among others, feature detection and tracking, optical flow and visual servoing, low-level stabilization and high-level planning methods. We then list popular low-cost UAVs, selecting mainly quadrotors. We discuss applications, restricting our focus to the field of infrastructure inspection. Finally, as an example, we formulate two use-cases for railway inspection, a less explored application field, and illustrate the usage of the vision and control techniques reviewed by selecting appropriate ones to tackle these use-cases. To select vision methods, we run a thorough set of experimental evaluations. PMID:26121608

High-Throughput Phenotyping of Plant Height: Comparing Unmanned Aerial Vehicles and Ground LiDAR Estimates.

PubMed

Madec, Simon; Baret, Fred; de Solan, Benoît; Thomas, Samuel; Dutartre, Dan; Jezequel, Stéphane; Hemmerlé, Matthieu; Colombeau, Gallian; Comar, Alexis

2017-01-01

The capacity of LiDAR and Unmanned Aerial Vehicles (UAVs) to provide plant height estimates as a high-throughput plant phenotyping trait was explored. An experiment over wheat genotypes conducted under well watered and water stress modalities was conducted. Frequent LiDAR measurements were performed along the growth cycle using a phénomobile unmanned ground vehicle. UAV equipped with a high resolution RGB camera was flying the experiment several times to retrieve the digital surface model from structure from motion techniques. Both techniques provide a 3D dense point cloud from which the plant height can be estimated. Plant height first defined as the z -value for which 99.5% of the points of the dense cloud are below. This provides good consistency with manual measurements of plant height (RMSE = 3.5 cm) while minimizing the variability along each microplot. Results show that LiDAR and structure from motion plant height values are always consistent. However, a slight under-estimation is observed for structure from motion techniques, in relation with the coarser spatial resolution of UAV imagery and the limited penetration capacity of structure from motion as compared to LiDAR. Very high heritability values ( H 2 > 0.90) were found for both techniques when lodging was not present. The dynamics of plant height shows that it carries pertinent information regarding the period and magnitude of the plant stress. Further, the date when the maximum plant height is reached was found to be very heritable ( H 2 > 0.88) and a good proxy of the flowering stage. Finally, the capacity of plant height as a proxy for total above ground biomass and yield is discussed.

High-Throughput Phenotyping of Plant Height: Comparing Unmanned Aerial Vehicles and Ground LiDAR Estimates

PubMed Central

Madec, Simon; Baret, Fred; de Solan, Benoît; Thomas, Samuel; Dutartre, Dan; Jezequel, Stéphane; Hemmerlé, Matthieu; Colombeau, Gallian; Comar, Alexis

2017-01-01

The capacity of LiDAR and Unmanned Aerial Vehicles (UAVs) to provide plant height estimates as a high-throughput plant phenotyping trait was explored. An experiment over wheat genotypes conducted under well watered and water stress modalities was conducted. Frequent LiDAR measurements were performed along the growth cycle using a phénomobile unmanned ground vehicle. UAV equipped with a high resolution RGB camera was flying the experiment several times to retrieve the digital surface model from structure from motion techniques. Both techniques provide a 3D dense point cloud from which the plant height can be estimated. Plant height first defined as the z-value for which 99.5% of the points of the dense cloud are below. This provides good consistency with manual measurements of plant height (RMSE = 3.5 cm) while minimizing the variability along each microplot. Results show that LiDAR and structure from motion plant height values are always consistent. However, a slight under-estimation is observed for structure from motion techniques, in relation with the coarser spatial resolution of UAV imagery and the limited penetration capacity of structure from motion as compared to LiDAR. Very high heritability values (H2> 0.90) were found for both techniques when lodging was not present. The dynamics of plant height shows that it carries pertinent information regarding the period and magnitude of the plant stress. Further, the date when the maximum plant height is reached was found to be very heritable (H2> 0.88) and a good proxy of the flowering stage. Finally, the capacity of plant height as a proxy for total above ground biomass and yield is discussed. PMID:29230229

Architecting Human Operator Trust in Automation to Improve System Effectiveness in Multiple Unmanned Aerial Vehicles (UAV) Control

DTIC Science & Technology

2009-03-01

like to extend our appreciation to our research sponsor Dr. Janet Miller from the Air Force Research Labs, and her colleague Dr. Cheryl Batchelor, for...for single-operator control of multiple UAVs. Drs. Brian Tsou, Lamar Warfield , Justin Estepp and Benjamin Knott , meanwhile, contributed to our

Real-Time Reliability Verification for UAV Flight Control System Supporting Airworthiness Certification.

PubMed

Xu, Haiyang; Wang, Ping

2016-01-01

In order to verify the real-time reliability of unmanned aerial vehicle (UAV) flight control system and comply with the airworthiness certification standard, we proposed a model-based integration framework for modeling and verification of time property. Combining with the advantages of MARTE, this framework uses class diagram to create the static model of software system, and utilizes state chart to create the dynamic model. In term of the defined transformation rules, the MARTE model could be transformed to formal integrated model, and the different part of the model could also be verified by using existing formal tools. For the real-time specifications of software system, we also proposed a generating algorithm for temporal logic formula, which could automatically extract real-time property from time-sensitive live sequence chart (TLSC). Finally, we modeled the simplified flight control system of UAV to check its real-time property. The results showed that the framework could be used to create the system model, as well as precisely analyze and verify the real-time reliability of UAV flight control system.

Real-Time Reliability Verification for UAV Flight Control System Supporting Airworthiness Certification

PubMed Central

Xu, Haiyang; Wang, Ping

2016-01-01

In order to verify the real-time reliability of unmanned aerial vehicle (UAV) flight control system and comply with the airworthiness certification standard, we proposed a model-based integration framework for modeling and verification of time property. Combining with the advantages of MARTE, this framework uses class diagram to create the static model of software system, and utilizes state chart to create the dynamic model. In term of the defined transformation rules, the MARTE model could be transformed to formal integrated model, and the different part of the model could also be verified by using existing formal tools. For the real-time specifications of software system, we also proposed a generating algorithm for temporal logic formula, which could automatically extract real-time property from time-sensitive live sequence chart (TLSC). Finally, we modeled the simplified flight control system of UAV to check its real-time property. The results showed that the framework could be used to create the system model, as well as precisely analyze and verify the real-time reliability of UAV flight control system. PMID:27918594

Nonlinear automatic landing control of unmanned aerial vehicles on moving platforms via a 3D laser radar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hervas, Jaime Rubio; Tang, Hui; Reyhanoglu, Mahmut

2014-12-10

This paper presents a motion tracking and control system for automatically landing Unmanned Aerial Vehicles (UAVs) on an oscillating platform using Laser Radar (LADAR) observations. The system itself is assumed to be mounted on a ship deck. A full nonlinear mathematical model is first introduced for the UAV. The ship motion is characterized by a Fourier transform based method which includes a realistic characterization of the sea waves. LADAR observation models are introduced and an algorithm to process those observations for yielding the relative state between the vessel and the UAV is presented, from which the UAV's state relative tomore » an inertial frame can be obtained and used for feedback purposes. A sliding mode control algorithm is derived for tracking a landing trajectory defined by a set of desired waypoints. An extended Kalman filter (EKF) is proposed to account for process and observation noises in the design of a state estimator. The effectiveness of the control algorithm is illustrated through a simulation example.« less

Calibration and Extension of a Discrete Event Operations Simulation Modeling Multiple Un-Manned Aerial Vehicles Controlled by a Single Operator

DTIC Science & Technology

2013-03-01

within systems of UAVs and between UAVs and the operators that use them. The next step for small UAVs in this direction is for one operator to be able...Team’s testing efforts, both in the planning and execution stages. The flight tests would never have taken place without the tremendous assistance...1 1.2 Unmanned Aerial Systems

Real-time target tracking and locating system for UAV

NASA Astrophysics Data System (ADS)

Zhang, Chao; Tang, Linbo; Fu, Huiquan; Li, Maowen

2017-07-01

In order to achieve real-time target tracking and locating for UAV, a reliable processing system is built on the embedded platform. Firstly, the video image is acquired in real time by the photovoltaic system on the UAV. When the target information is known, KCF tracking algorithm is adopted to track the target. Then, the servo is controlled to rotate with the target, when the target is in the center of the image, the laser ranging module is opened to obtain the distance between the UAV and the target. Finally, to combine with UAV flight parameters obtained by BeiDou navigation system, through the target location algorithm to calculate the geodetic coordinates of the target. The results show that the system is stable for real-time tracking of targets and positioning.

Design of UAV high resolution image transmission system

NASA Astrophysics Data System (ADS)

Gao, Qiang; Ji, Ming; Pang, Lan; Jiang, Wen-tao; Fan, Pengcheng; Zhang, Xingcheng

2017-02-01

In order to solve the problem of the bandwidth limitation of the image transmission system on UAV, a scheme with image compression technology for mini UAV is proposed, based on the requirements of High-definition image transmission system of UAV. The video codec standard H.264 coding module and key technology was analyzed and studied for UAV area video communication. Based on the research of high-resolution image encoding and decoding technique and wireless transmit method, The high-resolution image transmission system was designed on architecture of Android and video codec chip; the constructed system was confirmed by experimentation in laboratory, the bit-rate could be controlled easily, QoS is stable, the low latency could meets most applied requirement not only for military use but also for industrial applications.

Using Unmanned Aerial Vehicle (UAV) for spatio-temporal monitoring of soil erosion and roughness in Chania, Crete, Greece

NASA Astrophysics Data System (ADS)

Alexakis, Dimitrios; Seiradakis, Kostas; Tsanis, Ioannis

2016-04-01

This article presents a remote sensing approach for spatio-temporal monitoring of both soil erosion and roughness using an Unmanned Aerial Vehicle (UAV). Soil erosion by water is commonly known as one of the main reasons for land degradation. Gully erosion causes considerable soil loss and soil degradation. Furthermore, quantification of soil roughness (irregularities of the soil surface due to soil texture) is important and affects surface storage and infiltration. Soil roughness is one of the most susceptible to variation in time and space characteristics and depends on different parameters such as cultivation practices and soil aggregation. A UAV equipped with a digital camera was employed to monitor soil in terms of erosion and roughness in two different study areas in Chania, Crete, Greece. The UAV followed predicted flight paths computed by the relevant flight planning software. The photogrammetric image processing enabled the development of sophisticated Digital Terrain Models (DTMs) and ortho-image mosaics with very high resolution on a sub-decimeter level. The DTMs were developed using photogrammetric processing of more than 500 images acquired with the UAV from different heights above the ground level. As the geomorphic formations can be observed from above using UAVs, shadowing effects do not generally occur and the generated point clouds have very homogeneous and high point densities. The DTMs generated from UAV were compared in terms of vertical absolute accuracies with a Global Navigation Satellite System (GNSS) survey. The developed data products were used for quantifying gully erosion and soil roughness in 3D as well as for the analysis of the surrounding areas. The significant elevation changes from multi-temporal UAV elevation data were used for estimating diachronically soil loss and sediment delivery without installing sediment traps. Concerning roughness, statistical indicators of surface elevation point measurements were estimated and various parameters such as standard deviation of DTM, deviation of residual and standard deviation of prominence were calculated directly from the extracted DTM. Sophisticated statistical filters and elevation indices were developed to quantify both soil erosion and roughness. The applied methodology for monitoring both soil erosion and roughness provides an optimum way of reducing the existing gap between field scale and satellite scale. Keywords : UAV, soil, erosion, roughness, DTM

Fleets of enduring drones to probe atmospheric phenomena with clouds

NASA Astrophysics Data System (ADS)

Lacroix, Simon; Roberts, Greg; Benard, Emmanuel; Bronz, Murat; Burnet, Frédéric; Bouhoubeiny, Elkhedim; Condomines, Jean-Philippe; Doll, Carsten; Hattenberger, Gautier; Lamraoui, Fayçal; Renzaglia, Alessandro; Reymann, Christophe

2016-04-01

A full spatio-temporal four-dimensional characterization of the microphysics and dynamics of cloud formation including the onset of precipitation has never been reached. Such a characterization would yield a better understanding of clouds, e.g. to assess the dominant mixing mechanism and the main source of cloudy updraft dilution. It is the sampling strategy that matters: fully characterizing the evolution over time of the various parameters (P, T, 3D wind, liquid water content, aerosols...) within a cloud volume requires dense spatial sampling for durations of the order of one hour. A fleet of autonomous lightweight UAVs that coordinate themselves in real-time as an intelligent network can fulfill this purpose. The SkyScanner project targets the development of a fleet of autonomous UAVs to adaptively sample cumuli, so as to provide relevant data to address long standing questions in atmospheric science. It mixes basic researches and experimental developments, and gathers scientists in UAV conception, in optimal flight control, in intelligent cooperative behaviors, and of course atmospheric scientists. Two directions of researches are explored: optimal UAV conception and control, and optimal control of a fleet of UAVs. The design of UAVs for atmospheric science involves the satisfaction of trade-offs between payload, endurance, ease of deployment... A rational conception scheme that integrates the constraints to optimize a series of criteria, in particular energy consumption, would yield the definition of efficient UAVs. This requires a fine modeling of each involved sub-system and phenomenon, from the motor/propeller efficiency to the aerodynamics at small scale, including the flight control algorithms. The definition of mission profiles is also essential, considering the aerodynamics of clouds, to allow energy harvesting schemes that exploit thermals or gusts. The conception also integrates specific sensors, in particular wind sensor, for which classic technologies are challenged at the low speeds of lightweight UAVs. The overall control of the fleet so as to gather series of synchronized data in the cloud volume is a poorly informed and highly constrained adaptive sampling problem, in which the UAV motions must be defined to maximize the amount of gathered information and the mission duration. The overall approach casts the problem in a hierarchy of two modeling and decision stages. A macroscopic parametrized model of the cloud is built from the gathered data and exploited at the higher level by an operator, who sets information gathering goals. A subset of the UAV fleet is allocated to each goal, considering the current fleet state. These high level goals are handled by the lower level, which autonomously optimizes the selected UAVs trajectories using an on-line updated dense model of the variables of interest. Building the models involves Gaussian processes techniques (kriging) to fuse the gathered data with a generic cumulus conceptual model, the latter being defined from thorough statistics on realistic MesoNH cloud simulations. The model is exploited by a planner to generate trajectories that minimize the uncertainty in the map, while steering the vehicles within the air flows to save energy.

Pheromone-based coordination strategy to static sensors on the ground and unmanned aerial vehicles carried sensors

NASA Astrophysics Data System (ADS)

Pignaton de Freitas, Edison; Heimfarth, Tales; Pereira, Carlos Eduardo; Morado Ferreira, Armando; Rech Wagner, Flávio; Larsson, Tony

2010-04-01

A current trend that is gaining strength in the wireless sensor network area is the use of heterogeneous sensor nodes in one coordinated overall network, needed to fulfill the requirements of sophisticated emerging applications, such as area surveillance systems. One of the main concerns when developing such sensor networks is how to provide coordination among the heterogeneous nodes, in order to enable them to efficiently respond the user needs. This study presents an investigation of strategies to coordinate a set of static sensor nodes on the ground cooperating with wirelessly connected Unmanned Aerial Vehicles (UAVs) carrying a variety of sensors, in order to provide efficient surveillance over an area of interest. The sensor nodes on the ground are set to issue alarms on the occurrence of a given event of interest, e.g. entrance of a non-authorized vehicle in the area, while the UAVs receive the issued alarms and have to decide which of them is the most suitable to handle the issued alarm. A bio-inspired coordination strategy based on the concept of pheromones is presented. As a complement of this strategy, a utility-based decision making approach is proposed.

Fluxgate vector magnetometers: Compensated multi-sensor devices for ground, UAV and airborne magnetic survey for various application in near surface geophysics

NASA Astrophysics Data System (ADS)

Gavazzi, Bruno; Le Maire, Pauline; Munschy, Marc; Dechamp, Aline

2017-04-01

Fluxgate 3-components magnetometer is the kind of magnetometer which offers the lightest weight and lowest power consumption for the measurement of the intensity of the magnetic field. Moreover, vector measurements make it the only kind of magnetometer allowing compensation of magnetic perturbations due to the equipment carried with it. Unfortunately, Fluxgate magnetometers are quite uncommon in near surface geophysics due to the difficulty to calibrate them precisely. The recent advances in calibration of the sensors and magnetic compensation of the devices from a simple process on the field led Institut de Physique du Globe de Strasbourg to develop instruments for georeferenced magnetic measurements at different scales - from submetric measurements on the ground to aircraft-conducted acquisition through the wide range offered by unmanned aerial vehicles (UAVs) - with a precision in the order of 1 nT. Such equipment is used for different kind of application: structural geology, pipes and UXO detection, archaeology.

Fuzzy distributed cooperative tracking for a swarm of unmanned aerial vehicles with heterogeneous goals

NASA Astrophysics Data System (ADS)

Kladis, Georgios P.; Menon, Prathyush P.; Edwards, Christopher

2016-12-01

This article proposes a systematic analysis for a tracking problem which ensures cooperation amongst a swarm of unmanned aerial vehicles (UAVs), modelled as nonlinear systems with linear and angular velocity constraints, in order to achieve different goals. A distributed Takagi-Sugeno (TS) framework design is adopted for the representation of the nonlinear model of the dynamics of the UAVs. The distributed control law which is introduced is composed of both node and network level information. Firstly, feedback gains are synthesised using a parallel distributed compensation (PDC) control law structure, for a collection of isolated UAVs; ignoring communications among the swarm. Then secondly, based on an alternation-like procedure, the resulting feedback gains are used to determine Lyapunov matrices which are utilised at network level to incorporate into the control law, the relative differences in the states of the vehicles, and to induce cooperative behaviour. Eventually stability is guaranteed for the entire swarm. The control synthesis is performed using tools from linear control theory: in particular the design criteria are posed as linear matrix inequalities (LMIs). An example based on a UAV tracking scenario is included to outline the efficacy of the approach.

Estimating plant distance in maize using Unmanned Aerial Vehicle (UAV).

PubMed

Zhang, Jinshui; Basso, Bruno; Price, Richard F; Putman, Gregory; Shuai, Guanyuan

2018-01-01

Distance between rows and plants are essential parameters that affect the final grain yield in row crops. This paper presents the results of research intended to develop a novel method to quantify the distance between maize plants at field scale using an Unmanned Aerial Vehicle (UAV). Using this method, we can recognize maize plants as objects and calculate the distance between plants. We initially developed our method by training an algorithm in an indoor facility with plastic corn plants. Then, the method was scaled up and tested in a farmer's field with maize plant spacing that exhibited natural variation. The results of this study demonstrate that it is possible to precisely quantify the distance between maize plants. We found that accuracy of the measurement of the distance between maize plants depended on the height above ground level at which UAV imagery was taken. This study provides an innovative approach to quantify plant-to-plant variability and, thereby final crop yield estimates.

Investigation of 1 : 1,000 Scale Map Generation by Stereo Plotting Using Uav Images

NASA Astrophysics Data System (ADS)

Rhee, S.; Kim, T.

2017-08-01

Large scale maps and image mosaics are representative geospatial data that can be extracted from UAV images. Map drawing using UAV images can be performed either by creating orthoimages and digitizing them, or by stereo plotting. While maps generated by digitization may serve the need for geospatial data, many institutions and organizations require map drawing using stereoscopic vision on stereo plotting systems. However, there are several aspects to be checked for UAV images to be utilized for stereo plotting. The first aspect is the accuracy of exterior orientation parameters (EOPs) generated through automated bundle adjustment processes. It is well known that GPS and IMU sensors mounted on a UAV are not very accurate. It is necessary to adjust initial EOPs accurately using tie points. For this purpose, we have developed a photogrammetric incremental bundle adjustment procedure. The second aspect is unstable shooting conditions compared to aerial photographing. Unstable image acquisition may bring uneven stereo coverage, which will result in accuracy loss eventually. Oblique stereo pairs will create eye fatigue. The third aspect is small coverage of UAV images. This aspect will raise efficiency issue for stereo plotting of UAV images. More importantly, this aspect will make contour generation from UAV images very difficult. This paper will discuss effects relate to these three aspects. In this study, we tried to generate 1 : 1,000 scale map from the dataset using EOPs generated from software developed in-house. We evaluated Y-disparity of the tie points extracted automatically through the photogrammetric incremental bundle adjustment process. We could confirm that stereoscopic viewing is possible. Stereoscopic plotting work was carried out by a professional photogrammetrist. In order to analyse the accuracy of the map drawing using stereoscopic vision, we compared the horizontal and vertical position difference between adjacent models after drawing a specific model. The results of analysis showed that the errors were within the specification of 1 : 1,000 map. Although the Y-parallax can be eliminated, it is still necessary to improve the accuracy of absolute ground position error in order to apply this technique to the actual work. There are a few models in which the difference in height between adjacent models is about 40 cm. We analysed the stability of UAV images by checking angle differences between adjacent images. We also analysed the average area covered by one stereo model and discussed the possible difficulty associated with this narrow coverage. In the future we consider how to reduce position errors and improve map drawing performances from UAVs.

A Multi-Purpose Simulation Environment for UAV Research

DTIC Science & Technology

2003-05-01

Maximum 200 Words) Unmanned aerial vehicles (UAVs) are playing an important role in today’s military initiatives. UAVs have proven to be invaluable in...battlefield commanders. Integration of new technologies necessitates simulation prior to fielding new systems in order to avoid costly er- rors. The unique...collection ofinformation if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1. REPORT DATE (DD

Using Natural Language to Enable Mission Managers to Control Multiple Heterogeneous UAVs

NASA Technical Reports Server (NTRS)

Trujillo, Anna C.; Puig-Navarro, Javier; Mehdi, S. Bilal; Mcquarry, A. Kyle

2016-01-01

The availability of highly capable, yet relatively cheap, unmanned aerial vehicles (UAVs) is opening up new areas of use for hobbyists and for commercial activities. This research is developing methods beyond classical control-stick pilot inputs, to allow operators to manage complex missions without in-depth vehicle expertise. These missions may entail several heterogeneous UAVs flying coordinated patterns or flying multiple trajectories deconflicted in time or space to predefined locations. This paper describes the functionality and preliminary usability measures of an interface that allows an operator to define a mission using speech inputs. With a defined and simple vocabulary, operators can input the vast majority of mission parameters using simple, intuitive voice commands. Although the operator interface is simple, it is based upon autonomous algorithms that allow the mission to proceed with minimal input from the operator. This paper also describes these underlying algorithms that allow an operator to manage several UAVs.

Study of geomorphological changes by high quality DEMs, obtained from UAVs-Structure from Motion in highest continental cliffs of Europe: A Capelada (Galicia, Spain)

NASA Astrophysics Data System (ADS)

Muñoz Narciso, Efrén; García, Horacio; Sierra Pernas, Chema; Pérez-Alberti, Augusto

2017-04-01

This study analyses the geomorphological evolution of a highly dynamic coastal environment, one of the higher cliffs in Continental Europe (A Capelada, NW Spain), using Structure from Motion-Multi View Stereoscan techniques (hereafter referred to as SfM-MVS). Comparing orthoimages from the last 10 years we observed several topographical changes in one specific valley (Teixidelo). Interestingly, these changes were caused by 2 different processes: (i) heavy coastal erosion and (ii) slow complex landslides, working in opposite directions. The main challenge was obtaining high quality topographical data for quantifying the changes during the last few years using low cost-high quality techniques in remote areas. Unmanned Aerial Vehicle platforms (drones, hereafter referred to as UAVs) and SFM-MVS offer ultrahigh-density topographical data. Furthermore, the use of drones and SfM-MVS close range images requires new applications in geomorphology for understanding the workflow and limitations. In this paper we present the 2 main results: (i) a centimeter spatial resolution DEM from august 2016 was obtained using a @DJI Phantom 3 advanced model drone. The pictures were processed in Agisoft PhotoScan Pro 1.2.6 version by SfM-MVS techniques, generating a high-density point cloud (i.e. ˜2000 points/m2) with 3mm of RMSE (i.e. the point cloud was georeferenced in a geographical coordinates system using ˜40 Ground Control Points obtained from differential RTK-GPS and a Total Station network) and (ii) a DEM of Differences, which compares official freely available 2010 LiDAR data (i.e. ˜2 points/m2) with a 2016 DEM derived by UAVs-SfM, where we have observed meter-scale elevation changes (i.e. sediment and erosion processes). During this time, 75% of the sediment has been mobilized. The novel UAVs and SfM-MVS techniques prove to be great for advancing the study of geomorphological processes in remote areas.

Development and Implementation of Real-Time Information Delivery Systems for Emergency Management

NASA Technical Reports Server (NTRS)

Wegener, Steve; Sullivan, Don; Ambrosia, Vince; Brass, James; Dann, R. Scott

2000-01-01

The disaster management community has an on-going need for real-time data and information, especially during catastrophic events. Currently, twin engine or jet aircraft with limited altitude and duration capabilities collect much of the data. Flight safety is also an issue. Clearly, much of the needed data could be delivered via over-the-horizon transfer through a uninhabited aerial vehicles (UAV) platform to mission managers at various locations on the ground. In fact, because of the ability to stay aloft for long periods of time, and to fly above dangerous situations, UAV's are ideally suited for disaster missions. There are numerous situations that can be considered disastrous for the human population. Some, such as fire or flood, can continue over a period of days. Disaster management officials rely on data from the site to respond in an optimum way with warnings, evacuations, rescue, relief, and to the extent possible, damage control. Although different types of disasters call for different types of response, most situations can be improved by having visual images and other remotely sensed data available. "Disaster Management" is actually made up of a number of activities, including: - Disaster Prevention and Mitigation - Emergency Response Planning - Disaster Management (real-time deployment of resources, during an event) - Disaster / Risk Modeling All of these activities could benefit from real-time information, but a major focus for UAV-based technology is in real-time deployment of resources (i.e., emergency response teams), based on changing conditions at the location of the event. With all these potential benefits, it is desirable to demonstrate to user agencies the ability to perform disaster management missions as described. The following demonstration project is the first in a program designed to prove the feasibility of supporting disaster missions with UAV technology and suitable communications packages on-board. A several-year program is envisioned, in which a broad range of disaster-related activities are demonstrated to the appropriate user communities.

Fuzzy-Based Hybrid Control Algorithm for the Stabilization of a Tri-Rotor UAV.

PubMed

Ali, Zain Anwar; Wang, Daobo; Aamir, Muhammad

2016-05-09

In this paper, a new and novel mathematical fuzzy hybrid scheme is proposed for the stabilization of a tri-rotor unmanned aerial vehicle (UAV). The fuzzy hybrid scheme consists of a fuzzy logic controller, regulation pole-placement tracking (RST) controller with model reference adaptive control (MRAC), in which adaptive gains of the RST controller are being fine-tuned by a fuzzy logic controller. Brushless direct current (BLDC) motors are installed in the triangular frame of the tri-rotor UAV, which helps maintain control on its motion and different altitude and attitude changes, similar to rotorcrafts. MRAC-based MIT rule is proposed for system stability. Moreover, the proposed hybrid controller with nonlinear flight dynamics is shown in the presence of translational and rotational velocity components. The performance of the proposed algorithm is demonstrated via MATLAB simulations, in which the proposed fuzzy hybrid controller is compared with the existing adaptive RST controller. It shows that our proposed algorithm has better transient performance with zero steady-state error, and fast convergence towards stability.

A Generic, Agent-Based Framework for Design and Development of UAV/UCAV Control Systems

DTIC Science & Technology

2004-02-27

37 EID Principles .................................................................................................. 38 Experimental Support for EID...Year 2 Interface design and implementation; creation of the simulation environment; Year 3 Demonstration of the concept and experimental evaluation...UAV/UCAV control in which operators can experience high cognitive workloads. There are several ways in which systems can construct user models by

Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR

PubMed Central

Li, Jincheng; Chen, Jie; Wang, Pengbo; Li, Chunsheng

2018-01-01

In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner. PMID:29439447

Three-dimensional estimates of tree canopies: Scaling from high-resolution UAV data to satellite observations

NASA Astrophysics Data System (ADS)

Sankey, T.; Donald, J.; McVay, J.

2015-12-01

High resolution remote sensing images and datasets are typically acquired at a large cost, which poses big a challenge for many scientists. Northern Arizona University recently acquired a custom-engineered, cutting-edge UAV and we can now generate our own images with the instrument. The UAV has a unique capability to carry a large payload including a hyperspectral sensor, which images the Earth surface in over 350 spectral bands at 5 cm resolution, and a lidar scanner, which images the land surface and vegetation in 3-dimensions. Both sensors represent the newest available technology with very high resolution, precision, and accuracy. Using the UAV sensors, we are monitoring the effects of regional forest restoration treatment efforts. Individual tree canopy width and height are measured in the field and via the UAV sensors. The high-resolution UAV images are then used to segment individual tree canopies and to derive 3-dimensional estimates. The UAV image-derived variables are then correlated to the field-based measurements and scaled to satellite-derived tree canopy measurements. The relationships between the field-based and UAV-derived estimates are then extrapolated to a larger area to scale the tree canopy dimensions and to estimate tree density within restored and control forest sites.

Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR.

PubMed

Li, Jincheng; Chen, Jie; Wang, Pengbo; Li, Chunsheng

2018-02-11

In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner.

Neural network control of a parallel hybrid-electric propulsion system for a small unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Harmon, Frederick G.

2005-11-01

Parallel hybrid-electric propulsion systems would be beneficial for small unmanned aerial vehicles (UAVs) used for military, homeland security, and disaster-monitoring missions. The benefits, due to the hybrid and electric-only modes, include increased time-on-station and greater range as compared to electric-powered UAVs and stealth modes not available with gasoline-powered UAVs. This dissertation contributes to the research fields of small unmanned aerial vehicles, hybrid-electric propulsion system control, and intelligent control. A conceptual design of a small UAV with a parallel hybrid-electric propulsion system is provided. The UAV is intended for intelligence, surveillance, and reconnaissance (ISR) missions. A conceptual design reveals the trade-offs that must be considered to take advantage of the hybrid-electric propulsion system. The resulting hybrid-electric propulsion system is a two-point design that includes an engine primarily sized for cruise speed and an electric motor and battery pack that are primarily sized for a slower endurance speed. The electric motor provides additional power for take-off, climbing, and acceleration and also serves as a generator during charge-sustaining operation or regeneration. The intelligent control of the hybrid-electric propulsion system is based on an instantaneous optimization algorithm that generates a hyper-plane from the nonlinear efficiency maps for the internal combustion engine, electric motor, and lithium-ion battery pack. The hyper-plane incorporates charge-depletion and charge-sustaining strategies. The optimization algorithm is flexible and allows the operator/user to assign relative importance between the use of gasoline, electricity, and recharging depending on the intended mission. A MATLAB/Simulink model was developed to test the control algorithms. The Cerebellar Model Arithmetic Computer (CMAC) associative memory neural network is applied to the control of the UAVs parallel hybrid-electric propulsion system. The CMAC neural network approximates the hyper-plane generated from the instantaneous optimization algorithm and produces torque commands for the internal combustion engine and electric motor. The CMAC neural network controller saves on the required memory as compared to a large look-up table by two orders of magnitude. The CMAC controller also prevents the need to compute a hyper-plane or complex logic every time step.

Detail design of empennage of an unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Sarker, Md. Samad; Panday, Shoyon; Rasel, Md; Salam, Md. Abdus; Faisal, Kh. Md.; Farabi, Tanzimul Hasan

2017-12-01

In order to maintain the operational continuity of air defense systems, unmanned autonomous or remotely controlled unmanned aerial vehicle (UAV) plays a great role as a target for the anti-aircraft weapons. The aerial vehicle must comply with the requirements of high speed, remotely controlled tracking and navigational aids, operational sustainability and sufficient loiter time. It can also be used for aerial reconnaissance, ground surveillance and other intelligence operations. This paper aims to develop a complete tail design of an unmanned aerial vehicle using Systems Engineering approach. The design fulfils the requirements of longitudinal and directional trim, stability and control provided by the horizontal and vertical tail. Tail control surfaces are designed to provide sufficient control of the aircraft in critical conditions. Design parameters obtained from wing design are utilized in the tail design process as required. Through chronological calculations and successive iterations, optimum values of 26 tail design parameters are determined.

Automatic detection and counting of cattle in UAV imagery based on machine vision technology (Conference Presentation)

NASA Astrophysics Data System (ADS)

Rahnemoonfar, Maryam; Foster, Jamie; Starek, Michael J.

2017-05-01

Beef production is the main agricultural industry in Texas, and livestock are managed in pasture and rangeland which are usually huge in size, and are not easily accessible by vehicles. The current research method for livestock location identification and counting is visual observation which is very time consuming and costly. For animals on large tracts of land, manned aircraft may be necessary to count animals which is noisy and disturbs the animals, and may introduce a source of error in counts. Such manual approaches are expensive, slow and labor intensive. In this paper we study the combination of small unmanned aerial vehicle (sUAV) and machine vision technology as a valuable solution to manual animal surveying. A fixed-wing UAV fitted with GPS and digital RGB camera for photogrammetry was flown at the Welder Wildlife Foundation in Sinton, TX. Over 600 acres were flown with four UAS flights and individual photographs used to develop orthomosaic imagery. To detect animals in UAV imagery, a fully automatic technique was developed based on spatial and spectral characteristics of objects. This automatic technique can even detect small animals that are partially occluded by bushes. Experimental results in comparison to ground-truth show the effectiveness of our algorithm.

Wildlife Multispecies Remote Sensing Using Visible and Thermal Infrared Imagery Acquired from AN Unmanned Aerial Vehicle (uav)

NASA Astrophysics Data System (ADS)

Chrétien, L.-P.; Théau, J.; Ménard, P.

2015-08-01

Wildlife aerial surveys require time and significant resources. Multispecies detection could reduce costs to a single census for species that coexist spatially. Traditional methods are demanding for observers in terms of concentration and are not adapted to multispecies censuses. The processing of multispectral aerial imagery acquired from an unmanned aerial vehicle (UAV) represents a potential solution for multispecies detection. The method used in this study is based on a multicriteria object-based image analysis applied on visible and thermal infrared imagery acquired from a UAV. This project aimed to detect American bison, fallow deer, gray wolves, and elks located in separate enclosures with a known number of individuals. Results showed that all bison and elks were detected without errors, while for deer and wolves, 0-2 individuals per flight line were mistaken with ground elements or undetected. This approach also detected simultaneously and separately the four targeted species even in the presence of other untargeted ones. These results confirm the potential of multispectral imagery acquired from UAV for wildlife census. Its operational application remains limited to small areas related to the current regulations and available technology. Standardization of the workflow will help to reduce time and expertise requirements for such technology.

Low Cost and Flexible UAV Deployment of Sensors

PubMed Central

Sørensen, Lars Yndal; Jacobsen, Lars Toft; Hansen, John Paulin

2017-01-01

This paper presents a platform for airborne sensor applications using low-cost, open-source components carried by an easy-to-fly unmanned aircraft vehicle (UAV). The system, available in open-source , is designed for researchers, students and makers for a broad range of exploration and data-collection needs. The main contribution is the extensible architecture for modularized airborne sensor deployment and real-time data visualisation. Our open-source Android application provides data collection, flight path definition and map tools. Total cost of the system is below 800 dollars. The flexibility of the system is illustrated by mapping the location of Bluetooth beacons (iBeacons) on a ground field and by measuring water temperature in a lake. PMID:28098819

Low Cost and Flexible UAV Deployment of Sensors.

PubMed

Sørensen, Lars Yndal; Jacobsen, Lars Toft; Hansen, John Paulin

2017-01-14

This paper presents a platform for airborne sensor applications using low-cost, open-source components carried by an easy-to-fly unmanned aircraft vehicle (UAV). The system, available in open-source , is designed for researchers, students and makers for a broad range of exploration and data-collection needs. The main contribution is the extensible architecture for modularized airborne sensor deployment and real-time data visualisation. Our open-source Android application provides data collection, flight path definition and map tools. Total cost of the system is below 800 dollars. The flexibility of the system is illustrated by mapping the location of Bluetooth beacons (iBeacons) on a ground field and by measuring water temperature in a lake.

New distributed radar technology based on UAV or UGV application

NASA Astrophysics Data System (ADS)

Molchanov, Pavlo A.; Contarino, Vincent M.

2013-05-01

Regular micro and nano radars cannot provide reliable tracking of low altitude low profile aerial targets in urban and mountain areas because of reflection and re-reflections from buildings and terrain. They become visible and vulnerable to guided missiles if positioned on a tower or blimp. Doppler radar cannot distinguish moving cars and small low altitude aerial targets in an urban area. A new concept of pocket size distributed radar technology based on the application of UAV (Unmanned Air Vehicles), UGV (Unmanned Ground Vehicles) is proposed for tracking of low altitude low profile aerial targets at short and medium distances for protection of stadium, camp, military facility in urban or mountain areas.

UAV observation of newly formed volcanic island, Nishinoshima, Japan, from a ship

NASA Astrophysics Data System (ADS)

Ohminato, T.; Kaneko, T.; Takagi, A.

2016-12-01

We conducted an aerial observation at Nishinoshima island, south of Japan, from Jun 7 to Jun 9, 2016 by using an Unmanned Aerial Vehicle (UAV), a radio controlled small helicopter. Takeoff and landing of the UAV was conducted on a ship. Nishinoshima is a small island, 130km west of Chichijima in Ogasawara Islands, Japan. New eruption started in November 2013 in a shallow sea approximately 400 m southeast of the existing Nishinoshima Island. It started from a small islet and evolved with 1-5 × 105 m3/day discharge rate (Maeno et al, 2016). In late December 2013, the islet coalesced with the existing Nishinoshima. In 16 month, the lava field reached 2.6×106 m2and covered almost all of the existing Nishinoshima. Human landing upon the newly formed part of the island has still been prohibited due to the danger of sudden eruptions. Before our mission, some pumice or rock samples had been taken from the island but their amount was not enough to conduct detailed petrological analyses. The evolution of the lava field from the central cone has been well documented by using images taken from satellites and airplanes. However, due to the limited resolution of satellite images or photos taken from distant airplanes, there still be uncertainties in detailed morphological evolution of lava flows. The purpose of our observation includes, 1) sampling of pyroclasts near the central cone in order to investigate the condition of magma chamber and magma ascent process, and 2) taking high resolution 4K images in order to clarify the characteristic morphology of the lava flow covering the island. During the three days operation, we were successfully able to sample 250g of pyroclasts and to take 1.5TB of 4K movies. Conducting UAV's takeoff and landing on a ship was not an easy task. We used a marine research ship, Keifu-Maru, operated by Japan Meteorological Agency. The ship size is 1483 tons. On the ship deck, there are several structures which can interfere with the helicopter flights. During the UAV operation, the ship kept the lowest velocity but it was always pitching, yawing and rolling. Takeoff or landing on the ship were far more difficult than those on the ground at complete rest. In the presentation, we will show the difficulty in operating the UAV on the ship and how we overcame the difficulties.

Multispectral data processing from unmanned aerial vehicles: application in precision agriculture using different sensors and platforms

NASA Astrophysics Data System (ADS)

Piermattei, Livia; Bozzi, Carlo Alberto; Mancini, Adriano; Tassetti, Anna Nora; Karel, Wilfried; Pfeifer, Norbert

2017-04-01

Unmanned aerial vehicles (UAVs) in combination with consumer grade cameras have become standard tools for photogrammetric applications and surveying. The recent generation of multispectral, cost-efficient and lightweight cameras has fostered a breakthrough in the practical application of UAVs for precision agriculture. For this application, multispectral cameras typically use Green, Red, Red-Edge (RE) and Near Infrared (NIR) wavebands to capture both visible and invisible images of crops and vegetation. These bands are very effective for deriving characteristics like soil productivity, plant health and overall growth. However, the quality of results is affected by the sensor architecture, the spatial and spectral resolutions, the pattern of image collection, and the processing of the multispectral images. In particular, collecting data with multiple sensors requires an accurate spatial co-registration of the various UAV image datasets. Multispectral processed data in precision agriculture are mainly presented as orthorectified mosaics used to export information maps and vegetation indices. This work aims to investigate the acquisition parameters and processing approaches of this new type of image data in order to generate orthoimages using different sensors and UAV platforms. Within our experimental area we placed a grid of artificial targets, whose position was determined with differential global positioning system (dGPS) measurements. Targets were used as ground control points to georeference the images and as checkpoints to verify the accuracy of the georeferenced mosaics. The primary aim is to present a method for the spatial co-registration of visible, Red-Edge, and NIR image sets. To demonstrate the applicability and accuracy of our methodology, multi-sensor datasets were collected over the same area and approximately at the same time using the fixed-wing UAV senseFly "eBee". The images were acquired with the camera Canon S110 RGB, the multispectral cameras Canon S110 NIR and S110 RE and with the multi-camera system Parrot Sequoia, which is composed of single-band cameras (Green, Red, Red Edge, NIR and RGB). Imagery from each sensor was georeferenced and mosaicked with the commercial software Agisoft PhotoScan Pro and different approaches for image orientation were compared. To assess the overall spatial accuracy of each dataset the root mean square error was computed between check point coordinates measured with dGPS and coordinates retrieved from georeferenced image mosaics. Additionally, image datasets from different UAV platforms (i.e. DJI Phantom 4Pro, DJI Phantom 3 professional, and DJI Inspire 1 Pro) were acquired over the same area and the spatial accuracy of the orthoimages was evaluated.

Comparison of 3D point clouds produced by LIDAR and UAV photoscan in the Rochefort cave (Belgium)

NASA Astrophysics Data System (ADS)

Watlet, Arnaud; Triantafyllou, Antoine; Kaufmann, Olivier; Le Mouelic, Stéphane

2016-04-01

Amongst today's techniques that are able to produce 3D point clouds, LIDAR and UAV (Unmanned Aerial Vehicle) photogrammetry are probably the most commonly used. Both methods have their own advantages and limitations. LIDAR scans create high resolution and high precision 3D point clouds, but such methods are generally costly, especially for sporadic surveys. Compared to LIDAR, UAV (e.g. drones) are cheap and flexible to use in different kind of environments. Moreover, the photogrammetric processing workflow of digital images taken with UAV becomes easier with the rise of many affordable software packages (e.g. Agisoft, PhotoModeler3D, VisualSFM). We present here a challenging study made at the Rochefort Cave Laboratory (South Belgium) comprising surface and underground surveys. The site is located in the Belgian Variscan fold-and-thrust belt, a region that shows many karstic networks within Devonian limestone units. A LIDAR scan has been acquired in the main chamber of the cave (~ 15000 m³) to spatialize 3D point cloud of its inner walls and infer geological beds and structures. Even if the use of LIDAR instrument was not really comfortable in such caving environment, the collected data showed a remarkable precision according to few control points geometry. We also decided to perform another challenging survey of the same cave chamber by modelling a 3D point cloud using photogrammetry of a set of DSLR camera pictures taken from the ground and UAV pictures. The aim was to compare both techniques in terms of (i) implementation of data acquisition and processing, (ii) quality of resulting 3D points clouds (points density, field vs cloud recovery and points precision), (iii) their application for geological purposes. Through Rochefort case study, main conclusions are that LIDAR technique provides higher density point clouds with slightly higher precision than photogrammetry method. However, 3D data modeled by photogrammetry provide visible light spectral information for each modeled voxel and interpolated vertices that can be a useful attributes for clustering during data treatment. We thus illustrate such applications to the Rochefort cave by using both sources of 3D information to quantify the orientation of inaccessible geological structures (e.g. faults, tectonic and gravitational joints, and sediments bedding), cluster these structures using color information gathered from UAV's 3D point cloud and compare these data to structural data surveyed on the field. An additional drone photoscan was also conducted in the surface sinkhole giving access to the surveyed underground cavity to seek geological bodies' connections.

Optimising UAV topographic surveys processed with structure-from-motion: Ground control quality, quantity and bundle adjustment

NASA Astrophysics Data System (ADS)

James, M. R.; Robson, S.; d'Oleire-Oltmanns, S.; Niethammer, U.

2017-03-01

Structure-from-motion (SfM) algorithms greatly facilitate the production of detailed topographic models from photographs collected using unmanned aerial vehicles (UAVs). However, the survey quality achieved in published geomorphological studies is highly variable, and sufficient processing details are never provided to understand fully the causes of variability. To address this, we show how survey quality and consistency can be improved through a deeper consideration of the underlying photogrammetric methods. We demonstrate the sensitivity of digital elevation models (DEMs) to processing settings that have not been discussed in the geomorphological literature, yet are a critical part of survey georeferencing, and are responsible for balancing the contributions of tie and control points. We provide a Monte Carlo approach to enable geomorphologists to (1) carefully consider sources of survey error and hence increase the accuracy of SfM-based DEMs and (2) minimise the associated field effort by robust determination of suitable lower-density deployments of ground control. By identifying appropriate processing settings and highlighting photogrammetric issues such as over-parameterisation during camera self-calibration, processing artefacts are reduced and the spatial variability of error minimised. We demonstrate such DEM improvements with a commonly-used SfM-based software (PhotoScan), which we augment with semi-automated and automated identification of ground control points (GCPs) in images, and apply to two contrasting case studies - an erosion gully survey (Taroudant, Morocco) and an active landslide survey (Super-Sauze, France). In the gully survey, refined processing settings eliminated step-like artefacts of up to 50 mm in amplitude, and overall DEM variability with GCP selection improved from 37 to 16 mm. In the much more challenging landslide case study, our processing halved planimetric error to 0.1 m, effectively doubling the frequency at which changes in landslide velocity could be detected. In both case studies, the Monte Carlo approach provided a robust demonstration that field effort could by substantially reduced by only deploying approximately half the number of GCPs, with minimal effect on the survey quality. To reduce processing artefacts and promote confidence in SfM-based geomorphological surveys, published results should include processing details which include the image residuals for both tie points and GCPs, and ensure that these are considered appropriately within the workflow.

Planification de trajectoires pour une flotte d'UAVs

NASA Astrophysics Data System (ADS)

Ait El Cadi, Abdessamad

In this thesis we address the problem of coordinating and controlling a fleet of Unmanned Aerial Vehicles (UAVs) during a surveillance mission in a dynamic context. The problem is vast and is related to several scientific domains. We have studied three important parts of this problem: • modeling the ground with all its constraints; • computing a shortest non-holonomic continuous path in a risky environment with a presence of obstacles; • planning a surveillance mission for a fleet of UAVs in a real context. While investigating the scientific literature related to these topics, we have detected deficiencies in the modeling of the ground and in the computation of the shortest continuous path, two critical aspects for the planning of a mission. So after the literature review, we have proposed answers to these two aspects and have applied our developments to the planning of a mission of a fleet of UAVs in a risky environment with the presence of obstacles. Obstacles could be natural like mountain or any non flyable zone. We have first modeled the ground as a directed graph. However, instead of using a classic mesh, we opted for an intelligent modeling that reduces the computing time on the graph without losing accuracy. The proposed model is based on the concept of visibility graph, and it also takes into account the obstacles, the danger areas and the constraint of non-holonomy of the UAVs- the kinematic constraint of the planes that imposes a maximum steering angle. The graph is then cleaned to keep only the minimum information needed for the calculation of trajectories. The generation of this graph possibly requires a lot of computation time, but it is done only once before the planning and will not affect the performance of trajectory calculations. We have also developed another simpler graph that does not take into account the constraint of non-holonomy. The advantage of this second graph is that it reduces the computation time. However, it requires the use of a correction procedure to make the resulting trajectory non-holonomic. This correction is possible within the context of our missions, but not for all types of autonomous vehicles. Once the directed graph is generated, we propose the use of a procedure for calculating the shortest continuous non-holonomic path in a risky environment with the presence of obstacles. The directed graph already incorporates all the constraints, which makes it possible to model the problem as a shortest path problem with resource a resource constraint (the resource here is the amount of permitted risk). The results are very satisfactory since the resulting routes are non-holonomic paths that meet all constraints. Moreover, the computing time is very short. For cases based on the simpler graph, we have created a procedure for correcting the trajectory to make it non-holonomic. All calculations of non-holonomy are based on Dubins curves (1957). We have finally applied our results to the planning of a mission of a fleet of UAVs in a risky environment with the presence of obstacles. For this purpose, we have developed a directed multi-graph where, for each pair of targets (points of departure and return of the mission included), we calculate a series of shorter trajectories with different limits of risk -- from the risk-free path to the riskiest path. We then use a Tabu Search with two tabu lists. Using these procedures, we have been able to produce routes for a fleet of UAVs that minimize the cost of the mission while respecting the limit of risk and avoiding obstacles. Tests are conducted on examples created on the basis of descriptions given by the Canadian Defense and, also on some instances of the CVRP (Capacitated Vehicle Routing Problem), those described by Christofides et Elion and those described by Christofides, Mingozzi et Toth. The results are of very satisfactory since all trajectories are non-holonomic and the improvement of the objective, when compared to a simple constructive method, achieves in some cases between 10 % and 43 %. We have even obtained an improvement of 69 %, but on a poor solution generated by a greedy algorithm. (Abstract shortened by UMI.)

Mapping with MAV: Experimental Study on the Contribution of Absolute and Relative Aerial Position Control

NASA Astrophysics Data System (ADS)

Skaloud, J.; Rehak, M.; Lichti, D.

2014-03-01

This study highlights the benefit of precise aerial position control in the context of mapping using frame-based imagery taken by small UAVs. We execute several flights with a custom Micro Aerial Vehicle (MAV) octocopter over a small calibration field equipped with 90 signalized targets and 25 ground control points. The octocopter carries a consumer grade RGB camera, modified to insure precise GPS time stamping of each exposure, as well as a multi-frequency/constellation GNSS receiver. The GNSS antenna and camera are rigidly mounted together on a one-axis gimbal that allows control of the obliquity of the captured imagery. The presented experiments focus on including absolute and relative aerial control. We confirm practically that both approaches are very effective: the absolute control allows omission of ground control points while the relative requires only a minimum number of control points. Indeed, the latter method represents an attractive alternative in the context of MAVs for two reasons. First, the procedure is somewhat simplified (e.g. the lever-arm between the camera perspective and antenna phase centers does not need to be determined) and, second, its principle allows employing a single-frequency antenna and carrier-phase GNSS receiver. This reduces the cost of the system as well as the payload, which in turn increases the flying time.

Design of rapid prototype of UAV line-of-sight stabilized control system

NASA Astrophysics Data System (ADS)

Huang, Gang; Zhao, Liting; Li, Yinlong; Yu, Fei; Lin, Zhe

2018-01-01

The line-of-sight (LOS) stable platform is the most important technology of UAV (unmanned aerial vehicle), which can reduce the effect to imaging quality from vibration and maneuvering of the aircraft. According to the requirement of LOS stability system (inertial and optical-mechanical combined method) and UAV's structure, a rapid prototype is designed using based on industrial computer using Peripheral Component Interconnect (PCI) and Windows RTX to exchange information. The paper shows the control structure, and circuit system including the inertial stability control circuit with gyro and voice coil motor driven circuit, the optical-mechanical stability control circuit with fast-steering-mirror (FSM) driven circuit and image-deviation-obtained system, outer frame rotary follower, and information-exchange system on PC. Test results show the stability accuracy reaches 5μrad, and prove the effectiveness of the combined line-of-sight stabilization control system, and the real-time rapid prototype runs stable.

Uncertainty management for aerial vehicles: Coordination, deconfliction, and disturbance rejection

NASA Astrophysics Data System (ADS)

Panyakeow, Prachya

The presented dissertation aims to develop control algorithms that deal with three types of uncertainties managements. First, we examine the situation when unmanned aerial vehicles (UAVs) fly through uncertain environments that contain both stationary and moving obstacles. Moreover, a guarantee of collision avoidance is necessary when UAVs operate in close proximity of each other. Second, we look at the communication uncertainty among the network of cooperative UAVs and the efforts to establish and maintain the connectivity throughout their entire missions. Third, we explore the scenario when the aircraft flies through wind gust. The introduction of an appropriate control scheme to actively alleviate the gust loads can result into weight reduction and consequently lower the fuel cost. In the first part of this dissertation, we develop a deconfliction algorithm that guarantees collision avoidance between a pair of constant speed unicycle-type UAVs as well as convergence to the desired destination for each UAV in presence of static obstacles. We use a combination of navigation and swirling functions to direct the unicycle vehicles along the planned trajectories while avoiding inter-vehicle collisions. The main feature of our contribution is proposing means of designing a deconfliction algorithm for unicycle vehicles that more closely capture the dynamics of constant speed UAVs as opposed to double integrator models. Specifically, we consider the issue of UAV turn-rate constraints and proceed to explore the selection of key algorithmic parameters in order to minimize undesirable trajectories and overshoots induced by the avoidance algorithm. The avoidance and convergence analysis of the proposed algorithm is then performed for two cooperative UAVs and simulation results are provided to support the viability of the proposed framework for more general mission scenarios. For the uncertainty of the UAV network, we provides two approaches to establish connectivity among a collection of UAVs that are initially scattered in space. The goal is to find shortest trajectories that bring the UAVs to a connected formation where they are in the range of detection of one another and headed in the same direction to maintain the connectivity. Pontryagin Minimum Principle (PMP) is utilized to determine the control law and path synthesis for the UAVs under the turn-rate constraints. We introduce an algorithm to search for the optimal solution when the final network topology is specified; followed by a nonlinear programming method in which the final configuration is emerged from the optimization routine under the constraints that the final topology is connected. Each method has its own advantages based on the size of corporative networks. For the uncertainty due to gust turbulence, we choose a model predictive control (MPC) technique to address gust load alleviation (GLA) for a flexible aircraft. MPC is a discrete method based on repeated online optimization that allows direct consideration of control actuator constraints into the feedback computation. Gust alleviation systems are dependent on how the structural flexibility of the aircraft affects its dynamics. Hence, we develop a six-degree-of-freedom flexible aircraft model that can integrate rigid body dynamic with structural deflection. The structural stick-and-beam model is utilized for the calculation of aeroelastic mode shapes and airframe loads. Another important feature of MPC for GLA design is the ability to include the preview of gust information ahead of the aircraft nose into the prediction process. This helps raising the prediction accuracy and consequently improves the load alleviation performance. Finally, the aircraft is modified by the addition of the flap-array, a composition of small trailing edge flaps throughout the entire span of the wings. These flaps are used in conjunction with the distributed spoilers. With the availability of the control surfaces closer to the wing root, the MPC with flap-array can reduce the wing bending moment from different mode shapes and achieve better load alleviation performance than the original aircraft.

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

NASA Technical Reports Server (NTRS)

Dufrene, Warren R., Jr.

2004-01-01

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation thru the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The application of many different types of AI techniques for flight will be explored during this research effort. The research concentration will be directed to the application of different AI methods within the UAV arena. By evaluating AI approaches, which will include Expert Systems, Neural Networks, Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI techniques applied to achieving true autonomous operation of these systems thus providing new intellectual merit to this research field. The major area of discussion will be limited to the UAV. The systems of interest include small aircraft, insects, and miniature aircraft. Although flight systems will be explored, the benefits should apply to many Unmanned Vehicles such as: Rovers, Ocean Explorers, Robots, and autonomous operation systems. The flight system will be broken down into control agents that will represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework of applying a Security Overseer will be added in an attempt to address errors, emergencies, failures, damage, or over dynamic environment. The chosen control problem was the landing phase of UAV operation. The initial results from simulation in FlightGear are presented.

Curvature Continuous and Bounded Path Planning for Fixed-Wing UAVs

PubMed Central

Jiang, Peng; Li, Deshi; Sun, Tao

2017-01-01

Unmanned Aerial Vehicles (UAVs) play an important role in applications such as data collection and target reconnaissance. An accurate and optimal path can effectively increase the mission success rate in the case of small UAVs. Although path planning for UAVs is similar to that for traditional mobile robots, the special kinematic characteristics of UAVs (such as their minimum turning radius) have not been taken into account in previous studies. In this paper, we propose a locally-adjustable, continuous-curvature, bounded path-planning algorithm for fixed-wing UAVs. To deal with the curvature discontinuity problem, an optimal interpolation algorithm and a key-point shift algorithm are proposed based on the derivation of a curvature continuity condition. To meet the upper bound for curvature and to render the curvature extrema controllable, a local replanning scheme is designed by combining arcs and Bezier curves with monotonic curvature. In particular, a path transition mechanism is built for the replanning phase using minimum curvature circles for a planning philosophy. Numerical results demonstrate that the analytical planning algorithm can effectively generate continuous-curvature paths, while satisfying the curvature upper bound constraint and allowing UAVs to pass through all predefined waypoints in the desired mission region. PMID:28925960

Curvature Continuous and Bounded Path Planning for Fixed-Wing UAVs.

PubMed

Wang, Xiaoliang; Jiang, Peng; Li, Deshi; Sun, Tao

2017-09-19

Unmanned Aerial Vehicles (UAVs) play an important role in applications such as data collection and target reconnaissance. An accurate and optimal path can effectively increase the mission success rate in the case of small UAVs. Although path planning for UAVs is similar to that for traditional mobile robots, the special kinematic characteristics of UAVs (such as their minimum turning radius) have not been taken into account in previous studies. In this paper, we propose a locally-adjustable, continuous-curvature, bounded path-planning algorithm for fixed-wing UAVs. To deal with the curvature discontinuity problem, an optimal interpolation algorithm and a key-point shift algorithm are proposed based on the derivation of a curvature continuity condition. To meet the upper bound for curvature and to render the curvature extrema controllable, a local replanning scheme is designed by combining arcs and Bezier curves with monotonic curvature. In particular, a path transition mechanism is built for the replanning phase using minimum curvature circles for a planning philosophy. Numerical results demonstrate that the analytical planning algorithm can effectively generate continuous-curvature paths, while satisfying the curvature upper bound constraint and allowing UAVs to pass through all predefined waypoints in the desired mission region.

Secure Utilization of Beacons and UAVs in Emergency Response Systems for Building Fire Hazard

PubMed Central

Seo, Seung-Hyun; Choi, Jung-In; Song, Jinseok

2017-01-01

An intelligent emergency system for hazard monitoring and building evacuation is a very important application area in Internet of Things (IoT) technology. Through the use of smart sensors, such a system can provide more vital and reliable information to first-responders and also reduce the incidents of false alarms. Several smart monitoring and warning systems do already exist, though they exhibit key weaknesses such as a limited monitoring coverage and security, which have not yet been sufficiently addressed. In this paper, we propose a monitoring and emergency response method for buildings by utilizing beacons and Unmanned Aerial Vehicles (UAVs) on an IoT security platform. In order to demonstrate the practicability of our method, we also implement a proof of concept prototype, which we call the UAV-EMOR (UAV-assisted Emergency Monitoring and Response) system. Our UAV-EMOR system provides the following novel features: (1) secure communications between UAVs, smart sensors, the control server and a smartphone app for security managers; (2) enhanced coordination between smart sensors and indoor/outdoor UAVs to expand real-time monitoring coverage; and (3) beacon-aided rescue and building evacuation. PMID:28946659

Secure Utilization of Beacons and UAVs in Emergency Response Systems for Building Fire Hazard.

PubMed

Seo, Seung-Hyun; Choi, Jung-In; Song, Jinseok

2017-09-25

An intelligent emergency system for hazard monitoring and building evacuation is a very important application area in Internet of Things (IoT) technology. Through the use of smart sensors, such a system can provide more vital and reliable information to first-responders and also reduce the incidents of false alarms. Several smart monitoring and warning systems do already exist, though they exhibit key weaknesses such as a limited monitoring coverage and security, which have not yet been sufficiently addressed. In this paper, we propose a monitoring and emergency response method for buildings by utilizing beacons and Unmanned Aerial Vehicles (UAVs) on an IoT security platform. In order to demonstrate the practicability of our method, we also implement a proof of concept prototype, which we call the UAV-EMOR (UAV-assisted Emergency Monitoring and Response) system. Our UAV-EMOR system provides the following novel features: (1) secure communications between UAVs, smart sensors, the control server and a smartphone app for security managers; (2) enhanced coordination between smart sensors and indoor/outdoor UAVs to expand real-time monitoring coverage; and (3) beacon-aided rescue and building evacuation.

Vibration energy harvesting for unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Anton, Steven R.; Inman, Daniel J.

2008-03-01

Unmanned aerial vehicles (UAVs) are a critical component of many military operations. Over the last few decades, the evolution of UAVs has given rise to increasingly smaller aircraft. Along with the development of smaller UAVs, termed mini UAVs, has come issues involving the endurance of the aircraft. Endurance in mini UAVs is problematic because of the limited size of the fuel systems that can be incorporated into the aircraft. A large portion of the total mass of many electric powered mini UAVs, for example, is the rechargeable battery power source. Energy harvesting is an attractive technology for mini UAVs because it offers the potential to increase their endurance without adding significant mass or the need to increase the size of the fuel system. This paper investigates the possibility of harvesting vibration and solar energy in a mini UAV. Experimentation has been carried out on a remote controlled (RC) glider aircraft with a 1.8 m wing span. This aircraft was chosen to replicate the current electric mini UAVs used by the military today. The RC glider was modified to include two piezoelectric patches placed at the roots of the wings and a cantilevered piezoelectric beam installed in the fuselage to harvest energy from wing vibrations and rigid body motions of the aircraft, as well as two thin film photovoltaic panels attached to the top of the wings to harvest energy from sunlight. Flight testing has been performed and the power output of the piezoelectric and photovoltaic devices has been examined.

Photogrammetric Accuracy and Modeling of Rolling Shutter Cameras

NASA Astrophysics Data System (ADS)

Vautherin, Jonas; Rutishauser, Simon; Schneider-Zapp, Klaus; Choi, Hon Fai; Chovancova, Venera; Glass, Alexis; Strecha, Christoph

2016-06-01

Unmanned aerial vehicles (UAVs) are becoming increasingly popular in professional mapping for stockpile analysis, construction site monitoring, and many other applications. Due to their robustness and competitive pricing, consumer UAVs are used more and more for these applications, but they are usually equipped with rolling shutter cameras. This is a significant obstacle when it comes to extracting high accuracy measurements using available photogrammetry software packages. In this paper, we evaluate the impact of the rolling shutter cameras of typical consumer UAVs on the accuracy of a 3D reconstruction. Hereto, we use a beta-version of the Pix4Dmapper 2.1 software to compare traditional (non rolling shutter) camera models against a newly implemented rolling shutter model with respect to both the accuracy of geo-referenced validation points and to the quality of the motion estimation. Multiple datasets have been acquired using popular quadrocopters (DJI Phantom 2 Vision+, DJI Inspire 1 and 3DR Solo) following a grid flight plan. For comparison, we acquired a dataset using a professional mapping drone (senseFly eBee) equipped with a global shutter camera. The bundle block adjustment of each dataset shows a significant accuracy improvement on validation ground control points when applying the new rolling shutter camera model for flights at higher speed (8m=s). Competitive accuracies can be obtained by using the rolling shutter model, although global shutter cameras are still superior. Furthermore, we are able to show that the speed of the drone (and its direction) can be solely estimated from the rolling shutter effect of the camera.

a Sensor Aided H.264/AVC Video Encoder for Aerial Video Sequences with in the Loop Metadata Correction

NASA Astrophysics Data System (ADS)

Cicala, L.; Angelino, C. V.; Ruatta, G.; Baccaglini, E.; Raimondo, N.

2015-08-01

Unmanned Aerial Vehicles (UAVs) are often employed to collect high resolution images in order to perform image mosaicking and/or 3D reconstruction. Images are usually stored on board and then processed with on-ground desktop software. In such a way the computational load, and hence the power consumption, is moved on ground, leaving on board only the task of storing data. Such an approach is important in the case of small multi-rotorcraft UAVs because of their low endurance due to the short battery life. Images can be stored on board with either still image or video data compression. Still image system are preferred when low frame rates are involved, because video coding systems are based on motion estimation and compensation algorithms which fail when the motion vectors are significantly long and when the overlapping between subsequent frames is very small. In this scenario, UAVs attitude and position metadata from the Inertial Navigation System (INS) can be employed to estimate global motion parameters without video analysis. A low complexity image analysis can be still performed in order to refine the motion field estimated using only the metadata. In this work, we propose to use this refinement step in order to improve the position and attitude estimation produced by the navigation system in order to maximize the encoder performance. Experiments are performed on both simulated and real world video sequences.

Coordinated Autonomy for Persistent Presence in Harbor and Riverine Environments

DTIC Science & Technology

2007-09-30

estimators, and methods designed to deal with real-world problems such as video transmission noise; • OpenCV for basic computer vision functionality as...awareness and forward surveillance of Rocky’s intended path. Aerial video was transmitted to the UAV ground station, where an operator using GIS

Construction and Testing of Broadband High Impedance Ground Planes (HIGPS) for Surface Mount Antennas

DTIC Science & Technology

2008-03-01

Conductor PMC: Perfect Magnetic Conductor RF: Radio Frequency RH: Right-handed SNG : Single Negative TACAN: Tactical Air Navigation UAV: Unmanned Aerial...negative ( SNG ) and double-negative (DNG) materials, and their fascinating properties have driven the interest in MTMs (Engheta and Ziolkowski, 2006

A meta-analysis of human-system interfaces in unmanned aerial vehicle (UAV) swarm management.

PubMed

Hocraffer, Amy; Nam, Chang S

2017-01-01

A meta-analysis was conducted to systematically evaluate the current state of research on human-system interfaces for users controlling semi-autonomous swarms composed of groups of drones or unmanned aerial vehicles (UAVs). UAV swarms pose several human factors challenges, such as high cognitive demands, non-intuitive behavior, and serious consequences for errors. This article presents findings from a meta-analysis of 27 UAV swarm management papers focused on the human-system interface and human factors concerns, providing an overview of the advantages, challenges, and limitations of current UAV management interfaces, as well as information on how these interfaces are currently evaluated. In general allowing user and mission-specific customization to user interfaces and raising the swarm's level of autonomy to reduce operator cognitive workload are beneficial and improve situation awareness (SA). It is clear more research is needed in this rapidly evolving field. Copyright © 2016 Elsevier Ltd. All rights reserved.

IR radiation characteristics and operating range research for a quad-rotor unmanned aircraft vehicle.

PubMed

Gong, Mali; Guo, Rui; He, Sifeng; Wang, Wei

2016-11-01

The security threats caused by multi-rotor unmanned aircraft vehicles (UAVs) are serious, especially in public places. To detect and control multi-rotor UAVs, knowledge of IR characteristics is necessary. The IR characteristics of a typical commercial quad-rotor UAV are investigated in this paper through thermal imaging with an IR camera. Combining the 3D geometry and IR images of the UAV, a 3D IR characteristics model is established so that the radiant power from different views can be obtained. An estimation of operating range to detect the UAV is calculated theoretically using signal-to-noise ratio as the criterion. Field experiments are implemented with an uncooled IR camera in an environment temperature of 12°C and a uniform background. For the front view, the operating range is about 150 m, which is close to the simulation result of 170 m.

Detection of a Moving Gas Source and Estimation of its Concentration Field with a Sensing Aerial Vehicle Integration of Theoretical Controls and Computational Fluids

DTIC Science & Technology

2016-07-21

constants. The model (2.42) is popular for simulation of the UAV motion [60], [61], [62] due to the fact that it models the aircraft response to...inputs to the dynamic model (2.42). The concentration sensors onboard the UAV record concentration ( simulated ) data according to its spatial location...vehicle dynamics and guidance, and the onboard sensor modeling . 15. SUBJECT TERMS State estimation; UAVs , mobile sensors; grid adaptationj; plume

Maritime-Based UAVs: A Key to Success for the Joint Force Commander

DTIC Science & Technology

2015-05-18

both cases, the UAVs encountered icing conditions inevitably losing control and crashing into the water.xxiii Land-based UAVs as well as manned...www2.l- 3com.com/csw/ProductsAndServices/ DataSheets /VORTEX Sales-Sheet WEB.pdf. xxviii L3 Communication Systems, “ROVER 5 Handheld,” accessed on...May 2, 2015, http://www2.l-3com.com/csw/ProductsAndServices/ DataSheets /ROVER-5_Sales- Sheet_WEB.pdf. xxix National Research Council, Autonomous

Very high resolution crop surface models (CSMs) from UAV-based stereo images for rice growth monitoring In Northeast China

NASA Astrophysics Data System (ADS)

Bendig, J.; Willkomm, M.; Tilly, N.; Gnyp, M. L.; Bennertz, S.; Qiang, C.; Miao, Y.; Lenz-Wiedemann, V. I. S.; Bareth, G.

2013-08-01

Unmanned aerial vehicles (UAVs) became popular platforms for the collection of remotely sensed geodata in the last years (Hardin & Jensen 2011). Various applications in numerous fields of research like archaeology (Hendrickx et al., 2011), forestry or geomorphology evolved (Martinsanz, 2012). This contribution deals with the generation of multi-temporal crop surface models (CSMs) with very high resolution by means of low-cost equipment. The concept of the generation of multi-temporal CSMs using Terrestrial Laserscanning (TLS) has already been introduced by Hoffmeister et al. (2010). For this study, data acquisition was performed with a low-cost and low-weight Mini-UAV (< 5 kg). UAVs in general and especially smaller ones, like the system presented here, close a gap in small scale remote sensing (Berni et al., 2009; Watts et al., 2012). In precision agriculture frequent remote sensing on such scales during the vegetation period provides important spatial information on the crop status. Crop growth variability can be detected by comparison of the CSMs in different phenological stages. Here, the focus is on the detection of this variability and its dependency on cultivar and plant treatment. The method has been tested for data acquired on a barley experiment field in Germany. In this contribution, it is applied to a different crop in a different environment. The study area is an experiment field for rice in Northeast China (Sanjiang Plain). Three replications of the cultivars Kongyu131 and Longjing21 were planted in plots that were treated with different amounts of N-fertilizer. In July 2012 three UAV-campaigns were carried out. Establishment of ground control points (GCPs) allowed for ground truth. Additionally, further destructive and non-destructive field data were collected. The UAV-system is an MK-Okto by Hisystems (http://www.mikrokopter.de) which was equipped with the high resolution Panasonic Lumix GF3 12 megapixel consumer camera. The self-built and self-maintained system has a payload of up to 1 kg and an average flight time of 15 minutes. The maximum speed is around 30 km/h and the system can be operated up to a wind speed of less than 19 km/h (Beaufort scale number 3 for wind speed). Using a suitable flight plan stereo images can be captured. For this study, a flying height of 50 m and a 44% side and 90% forward overlap was chosen. The images are processed into CSMs under the use of the Structure from Motion (SfM)-based software Agisoft Photoscan 0.9.0. The resulting models have a resolution of 0.02 m and an average number of about 12 million points. Further data processing in Esri ArcGIS allows for quantitative comparison of the plant heights. The multi-temporal datasets are analysed on a plot size basis. The results can be compared to and combined with the additional field data. Detecting plant height with non-invasive measurement techniques enables analysis of its correlation to biomass and other crop parameters (Hansen & Schjoerring, 2003; Thenkabail et al., 2000) measured in the field. The method presented here can therefore be a valuable addition for the recognition of such correlations.

Geomorphology and vegetation mapping the ice-free terrains of the Western Antarctic Peninsula region using very high resolution imagery from an UAV

NASA Astrophysics Data System (ADS)

Vieira, G.; Mora, C.; Pina, P.; Bandeira, L.; Hong, S. G.

2014-12-01

The West Antarctic Peninsula (WAP) is one of the Earth's regions with a fastest warming signal since the 1950's with an increase of over +2.5 ºC in MAAT. Significant changes have been reported for glaciers, ice-shelves, sea-ice and also for the permafrost environment. Mapping and monitoring the ice-free areas of the WAP has been until recently limited by the available aerial photo surveys, but also by the scarce high resolution satellite imagery (e.g. QuickBird, WorldView, etc.) that are seriously constrained by the high cloudiness of the region. Recent developments in Unmanned Aerial Vehicles (UAV's), which have seen significant technological advances and price reduction in the last few years, allow for its systematical use for mapping and monitoring in remote environments. In the framework of projects PERMANTAR-3 (PTDC/AAG-GLO/3908/2012 - FCT) and 3DAntártida (Ciência Viva), we complement traditional terrain surveying and mapping, satellite remote sensing (SAR and optical) and D-GPS deformation monitoring, with the application of an UAV. In this communication, we present the results from the application of a Sensefly ebee UAV in mapping the vegetation and geomorphological processes (e.g. sorted circles), as well as for digital elevation model generation in a test site in Barton Pen., King George Isl.. The UAV is a lightweight (ci. 700g) aircraft, with a 96 cm wingspan, which is portable and easy to transport. It allows for up to 40 min flight time, with application of RGB or NIR cameras. We have tested the ebee successfully with winds up to 10 m/s and obtained aerial photos with a ground resolution of 4 cm/pixel. The digital orthophotomaps, high resolution DEM's together with field observations have allowed for deriving geomorphological maps with unprecedented detail and accuracy, providing new insight into the controls on the spatial distribution of geomorphological processes. The talk will focus on the first results from the field surveys of February and March 2014 and will also include some test data from the mountains of serra da Estrela, Portugal. New surveying is planned for the season of 2014-15 with mapping to be conducted in Livingston and King George Islands.

Comparison of a Fixed-Wing and Multi-Rotor Uav for Environmental Mapping Applications: a Case Study

NASA Astrophysics Data System (ADS)

Boon, M. A.; Drijfhout, A. P.; Tesfamichael, S.

2017-08-01

The advent and evolution of Unmanned Aerial Vehicles (UAVs) and photogrammetric techniques has provided the possibility for on-demand high-resolution environmental mapping. Orthoimages and three dimensional products such as Digital Surface Models (DSMs) are derived from the UAV imagery which is amongst the most important spatial information tools for environmental planning. The two main types of UAVs in the commercial market are fixed-wing and multi-rotor. Both have their advantages and disadvantages including their suitability for certain applications. Fixed-wing UAVs normally have longer flight endurance capabilities while multi-rotors can provide for stable image capturing and easy vertical take-off and landing. Therefore, the objective of this study is to assess the performance of a fixed-wing versus a multi-rotor UAV for environmental mapping applications by conducting a specific case study. The aerial mapping of the Cors-Air model aircraft field which includes a wetland ecosystem was undertaken on the same day with a Skywalker fixed-wing UAV and a Raven X8 multi-rotor UAV equipped with similar sensor specifications (digital RGB camera) under the same weather conditions. We compared the derived datasets by applying the DTMs for basic environmental mapping purposes such as slope and contour mapping including utilising the orthoimages for identification of anthropogenic disturbances. The ground spatial resolution obtained was slightly higher for the multi-rotor probably due to a slower flight speed and more images. The results in terms of the overall precision of the data was noticeably less accurate for the fixed-wing. In contrast, orthoimages derived from the two systems showed small variations. The multi-rotor imagery provided better representation of vegetation although the fixed-wing data was sufficient for the identification of environmental factors such as anthropogenic disturbances. Differences were observed utilising the respective DTMs for the mapping of the wetland slope and contour mapping including the representation of hydrological features within the wetland. Factors such as cost, maintenance and flight time is in favour of the Skywalker fixed-wing. The multi-rotor on the other hand is more favourable in terms of data accuracy including for precision environmental planning purposes although the quality of the data of the fixed-wing is satisfactory for most environmental mapping applications.

The Practical Application of Uav-Based Photogrammetry Under Economic Aspects

NASA Astrophysics Data System (ADS)

Sauerbier, M.; Siegrist, E.; Eisenbeiss, H.; Demir, N.

2011-09-01

Nowadays, small size UAVs (Unmanned Aerial Vehicles) have reached a level of practical reliability and functionality that enables this technology to enter the geomatics market as an additional platform for spatial data acquisition. Though one could imagine a wide variety of interesting sensors to be mounted on such a device, here we will focus on photogrammetric applications using digital cameras. In praxis, UAV-based photogrammetry will only be accepted if it a) provides the required accuracy and an additional value and b) if it is competitive in terms of economic application compared to other measurement technologies. While a) was already proven by the scientific community and results were published comprehensively during the last decade, b) still has to be verified under real conditions. For this purpose, a test data set representing a realistic scenario provided by ETH Zurich was used to investigate cost effectiveness and to identify weak points in the processing chain that require further development. Our investigations are limited to UAVs carrying digital consumer cameras, for larger UAVs equipped with medium format cameras the situation has to be considered as significantly different. Image data was acquired during flights using a microdrones MD4-1000 quadrocopter equipped with an Olympus PE-1 digital compact camera. From these images, a subset of 5 images was selected for processing in order to register the effort of time required for the whole production chain of photogrammetric products. We see the potential of mini UAV-based photogrammetry mainly in smaller areas, up to a size of ca. 100 hectares. Larger areas can be efficiently covered by small airplanes with few images, reducing processing effort drastically. In case of smaller areas of a few hectares only, it depends more on the products required. UAVs can be an enhancement or alternative to GNSS measurements, terrestrial laser scanning and ground based photogrammetry. We selected the above mentioned test data from a project featuring an area of interest within the practical range for mini UAVs. While flight planning and flight operation are already quite efficient processes, the bottlenecks identified are mainly related to image processing. Although we used specific software for image processing, the identified gaps in the processing chain today are valid for most commercial photogrammetric software systems on the market. An outlook proposing improvements for a practicable workflow applicable in projects in private economy will be given.

High resolution and low altitude magnetic surveys for structural geology mapping in the Seabee mine, Saskatchewan, Canada, using UAV-MAG™ technology.

NASA Astrophysics Data System (ADS)

Braun, A.; Parvar, K.; Burns, M.

2017-12-01

Uninhabited Aerial Vehicles (UAV) provide the operational flexibility and ease of use which makes them ideal tools for low altitude and high resolution magnetic surveys. Being able to fly at lower altitudes compared to manned aircrafts provides the proximity to the target needed to increase the sensitivity to detect smaller and less magnetic targets. Considering the same sensor specifications, this further increases the signal to noise ratio. However, to increase spatial resolution, a tighter line spacing is needed which increases the survey time. We describe a case study in the Seabee mine in Saskatchewan, Canada. Using Pioneer Exploration Ltd. UAV-MAG™ technology, we emphasize the importance of altitude and line spacing in magnetic surveys with UAVs in order to resolve smaller and less magnetic targets compared to conventional manned airborne magnetic surveys. Mapping lithological or stratigraphic changes along the target structure requires an existing gradient in magnetic susceptibility. Mostly, this criterium is either not presented or the is weaker than the sensor's signal to noise ratio at a certain flying altitude. However, the folded structure in the study region shows high susceptibility changes in rock formations in high altitude regional magnetic surveys. In order to confirm that there are no missed structural elements in the target region, a UAV magnetic survey using a GEM Systems GSMP-35A potassium vapor magnetometer on Pioneer Exploration's UAV-MAG™ platform was conducted to exploit the structure in detail and compare the gain in spatial resolution from flying at lower altitude and with denser flight lines. The survey was conducted at 25 meters above ground level (AGL). Line spacing was set to 15 meters and a total of 550 kilometers was covered using an autonomous UAV. The collected data were compared to the regional airborne data which were collected at 150 meters AGL with a line spacing of 100 meters. Comparison revealed an anticline with plunge in the northeastern side of the gird. The analysis of the magnetic data, both total magnetic intensity and gradients, reveals that the UAV survey is able to resolve much smaller structures than the manned airborne survey. These details also match observations made in previous geological mapping missions.

Fuzzy-Based Hybrid Control Algorithm for the Stabilization of a Tri-Rotor UAV

PubMed Central

Ali, Zain Anwar; Wang, Daobo; Aamir, Muhammad

2016-01-01

In this paper, a new and novel mathematical fuzzy hybrid scheme is proposed for the stabilization of a tri-rotor unmanned aerial vehicle (UAV). The fuzzy hybrid scheme consists of a fuzzy logic controller, regulation pole-placement tracking (RST) controller with model reference adaptive control (MRAC), in which adaptive gains of the RST controller are being fine-tuned by a fuzzy logic controller. Brushless direct current (BLDC) motors are installed in the triangular frame of the tri-rotor UAV, which helps maintain control on its motion and different altitude and attitude changes, similar to rotorcrafts. MRAC-based MIT rule is proposed for system stability. Moreover, the proposed hybrid controller with nonlinear flight dynamics is shown in the presence of translational and rotational velocity components. The performance of the proposed algorithm is demonstrated via MATLAB simulations, in which the proposed fuzzy hybrid controller is compared with the existing adaptive RST controller. It shows that our proposed algorithm has better transient performance with zero steady-state error, and fast convergence towards stability. PMID:27171084

Application of high resolution images from unmanned aerial vehicles for hydrology and rangeland science

NASA Astrophysics Data System (ADS)

Rango, A.; Vivoni, E. R.; Anderson, C. A.; Perini, N. A.; Saripalli, S.; Laliberte, A.

2012-12-01

A common problem in many natural resource disciplines is the lack of high-enough spatial resolution images that can be used for monitoring and modeling purposes. Advances have been made in the utilization of Unmanned Aerial Vehicles (UAVs) in hydrology and rangeland science. By utilizing low flight altitudes and velocities, UAVs are able to produce high resolution (5 cm) images as well as stereo coverage (with 75% forward overlap and 40% sidelap) to extract digital elevation models (DEM). Another advantage of flying at low altitude is that the potential problems of atmospheric haze obscuration are eliminated. Both small fixed-wing and rotary-wing aircraft have been used in our experiments over two rangeland areas in the Jornada Experimental Range in southern New Mexico and the Santa Rita Experimental Range in southern Arizona. The fixed-wing UAV has a digital camera in the wing and six-band multispectral camera in the nose, while the rotary-wing UAV carries a digital camera as payload. Because we have been acquiring imagery for several years, there are now > 31,000 photos at one of the study sites, and 177 mosaics over rangeland areas have been constructed. Using the DEM obtained from the imagery we have determined the actual catchment areas of three watersheds and compared these to previous estimates. At one site, the UAV-derived watershed area is 4.67 ha which is 22% smaller compared to a manual survey using a GPS unit obtained several years ago. This difference can be significant in constructing a watershed model of the site. From a vegetation species classification, we also determined that two of the shrub types in this small watershed(mesquite and creosote with 6.47 % and 5.82% cover, respectively) grow in similar locations(flat upland areas with deep soils), whereas the most predominant shrub(mariola with 11.9% cover) inhabits hillslopes near stream channels(with steep shallow soils). The positioning of these individual shrubs throughout the catchment using UAV image classifications is required as input to detailed watershed modeling There are multiple advantages to UAVs for use in hydrology and rangeland science, including that coverage is less expensive while just as accurate as conventional ground measurements. The UAV guidance systems can also guarantee returning to the same location for change detection analysis. UAV capabilities also have advantages over manned aircraft because they are safer, less expensive, and can respond in a timelier manner to new flight requests. As a result, the use of UAVs for watershed and rangeland monitoring and modeling is a rapidly expanding civil application in natural resources.

On-Board Mining in the Sensor Web

NASA Astrophysics Data System (ADS)

Tanner, S.; Conover, H.; Graves, S.; Ramachandran, R.; Rushing, J.

2004-12-01

On-board data mining can contribute to many research and engineering applications, including natural hazard detection and prediction, intelligent sensor control, and the generation of customized data products for direct distribution to users. The ability to mine sensor data in real time can also be a critical component of autonomous operations, supporting deep space missions, unmanned aerial and ground-based vehicles (UAVs, UGVs), and a wide range of sensor meshes, webs and grids. On-board processing is expected to play a significant role in the next generation of NASA, Homeland Security, Department of Defense and civilian programs, providing for greater flexibility and versatility in measurements of physical systems. In addition, the use of UAV and UGV systems is increasing in military, emergency response and industrial applications. As research into the autonomy of these vehicles progresses, especially in fleet or web configurations, the applicability of on-board data mining is expected to increase significantly. Data mining in real time on board sensor platforms presents unique challenges. Most notably, the data to be mined is a continuous stream, rather than a fixed store such as a database. This means that the data mining algorithms must be modified to make only a single pass through the data. In addition, the on-board environment requires real time processing with limited computing resources, thus the algorithms must use fixed and relatively small amounts of processing time and memory. The University of Alabama in Huntsville is developing an innovative processing framework for the on-board data and information environment. The Environment for On-Board Processing (EVE) and the Adaptive On-board Data Processing (AODP) projects serve as proofs-of-concept of advanced information systems for remote sensing platforms. The EVE real-time processing infrastructure will upload, schedule and control the execution of processing plans on board remote sensors. These plans provide capabilities for autonomous data mining, classification and feature extraction using both streaming and buffered data sources. A ground-based testbed provides a heterogeneous, embedded hardware and software environment representing both space-based and ground-based sensor platforms, including wireless sensor mesh architectures. The AODP project explores the EVE concepts in the world of sensor-networks, including ad-hoc networks of small sensor platforms.

Bridge Crack Detection Using Multi-Rotary Uav and Object-Base Image Analysis

NASA Astrophysics Data System (ADS)

Rau, J. Y.; Hsiao, K. W.; Jhan, J. P.; Wang, S. H.; Fang, W. C.; Wang, J. L.

2017-08-01

Bridge is an important infrastructure for human life. Thus, the bridge safety monitoring and maintaining is an important issue to the government. Conventionally, bridge inspection were conducted by human in-situ visual examination. This procedure sometimes require under bridge inspection vehicle or climbing under the bridge personally. Thus, its cost and risk is high as well as labor intensive and time consuming. Particularly, its documentation procedure is subjective without 3D spatial information. In order cope with these challenges, this paper propose the use of a multi-rotary UAV that equipped with a SONY A7r2 high resolution digital camera, 50 mm fixed focus length lens, 135 degrees up-down rotating gimbal. The target bridge contains three spans with a total of 60 meters long, 20 meters width and 8 meters height above the water level. In the end, we took about 10,000 images, but some of them were acquired by hand held method taken on the ground using a pole with 2-8 meters long. Those images were processed by Agisoft PhotoscanPro to obtain exterior and interior orientation parameters. A local coordinate system was defined by using 12 ground control points measured by a total station. After triangulation and camera self-calibration, the RMS of control points is less than 3 cm. A 3D CAD model that describe the bridge surface geometry was manually measured by PhotoscanPro. They were composed of planar polygons and will be used for searching related UAV images. Additionally, a photorealistic 3D model can be produced for 3D visualization. In order to detect cracks on the bridge surface, we utilize object-based image analysis (OBIA) technique to segment the image into objects. Later, we derive several object features, such as density, area/bounding box ratio, length/width ratio, length, etc. Then, we can setup a classification rule set to distinguish cracks. Further, we apply semi-global-matching (SGM) to obtain 3D crack information and based on image scale we can calculate the width of a crack object. For spalling volume calculation, we also apply SGM to obtain dense surface geometry. Assuming the background is a planar surface, we can fit a planar function and convert the surface geometry into a DSM. Thus, for spalling area its height will be lower than the plane and its value will be negative. We can thus apply several image processing technique to segment the spalling area and calculate the spalling volume as well. For bridge inspection and UAV image management within a laboratory, we develop a graphic user interface. The major functions include crack auto-detection using OBIA, crack editing, i.e. delete and add cracks, crack attributing, 3D crack visualization, spalling area/volume calculation, bridge defects documentation, etc.

Indicator Species Population Monitoring in Antarctica with Uav

NASA Astrophysics Data System (ADS)

Zmarz, A.; Korczak-Abshire, M.; Storvold, R.; Rodzewicz, M.; Kędzierska, I.

2015-08-01

A program to monitor bird and pinniped species in the vicinity of Arctowski Station, King George Island, South Shetlands, Antarctica, has been conducted over the past 38 years. Annual monitoring of these indicator species includes estimations of breeding population sizes of three Pygoscelis penguin species: Adélie, gentoo and chinstrap. Six penguin colonies situated on the western shores of two bays: Admiralty and King George are investigated. To study changes in penguin populations Unmanned Aerial Vehicles were used for the first time in the 2014/15 austral summer season. During photogrammetric flights the high-resolution images of eight penguin breeding colonies were taken. Obtained high resolution images were used for estimation of breeding population size and compared with the results of measurements taken at the same time from the ground. During this Antarctic expedition eight successful photogrammetry missions (total distance 1500 km) were performed. Images were taken with digital SLR Canon 700D, Nikon D5300, Nikon D5100 with a 35mm objective lens. Flights altitude at 350 - 400 AGL, allowed images to be taken with a resolution GSD (ground sample distance) less than 5 cm. The Image J software analysis method was tested to provide automatic population estimates from obtained images. The use of UAV for monitoring of indicator species, enabled data acquisition from areas inaccessible by ground methods.

Remote sensing for developing world agriculture: opportunities and areas for technical development

NASA Astrophysics Data System (ADS)

Jeunnette, Mark N.; Hart, Douglas P.

2016-10-01

A parameterized numerical model is constructed to compare platform options for collecting aerial imagery to support agriculture electronic information services in developing countries like India. A sensitivity analysis shows that when Unmanned Aerial Vehicles, UAVs, are limited in flight altitude by regulations, the velocity and altitude available to manned aircraft lead to a lower cost of operation at altitudes greater than 2000ft above ground level, AGL. If, however, the UAVs are allowed to fly higher, they become cost-competitive once again at approximately 1000ft AGL or higher. Examination of assumptions in the model highlights two areas for additional technology development: baseline-dependent feature-based image registration to enable wider area coverage, and reflectance reconstruction for ratio-based agriculture indices.

Near Real-Time Georeference of Umanned Aerial Vehicle Images for Post-Earthquake Response

NASA Astrophysics Data System (ADS)

Wang, S.; Wang, X.; Dou, A.; Yuan, X.; Ding, L.; Ding, X.

2018-04-01

The rapid collection of Unmanned Aerial Vehicle (UAV) remote sensing images plays an important role in the fast submitting disaster information and the monitored serious damaged objects after the earthquake. However, for hundreds of UAV images collected in one flight sortie, the traditional data processing methods are image stitching and three-dimensional reconstruction, which take one to several hours, and affect the speed of disaster response. If the manual searching method is employed, we will spend much more time to select the images and the find images do not have spatial reference. Therefore, a near-real-time rapid georeference method for UAV remote sensing disaster data is proposed in this paper. The UAV images are achieved georeference combined with the position and attitude data collected by UAV flight control system, and the georeferenced data is organized by means of world file which is developed by ESRI. The C # language is adopted to compile the UAV images rapid georeference software, combined with Geospatial Data Abstraction Library (GDAL). The result shows that it can realize rapid georeference of remote sensing disaster images for up to one thousand UAV images within one minute, and meets the demand of rapid disaster response, which is of great value in disaster emergency application.

The Altus Cumulus Electrification Study (ACES): A UAV-Based Science Demonstration

NASA Technical Reports Server (NTRS)

Blakeslee, R. J.; Croskey, C. L.; Desch, M. D.; Farrell, W. M.; Goldberg, R. A.; Houser, J. G.; Kim, H. S.; Mach, D. M.; Mitchell, J. D.; Stoneburner, J. C.

2003-01-01

The Altus Cumulus Electrification Study (ACES) is an unmanned aerial vehicle (UAV)- based project that investigated thunderstorms in the vicinity of the Florida Everglades in August 2002. ACES was conducted to investigate storm electrical activity and its relationship to storm morphology, and to validate satellite-based lightning measurements. In addition, as part of the NASA sponsored UAV-based science demonstration program, this project provided a scientifically useful demonstration of the utility and promise of UAV platforms for Earth science and applications observations. ACES employed the Altus II aircraft, built by General Atomics - Aeronautical Systems, Inc. Key science objectives simultaneously addressed by ACES are to: (1) investigate lightning-storm relationships, (2) study storm electrical budgets, and provide Lightning Imaging Sensor validation. The ACES payload included electrical, magnetic, and optical sensors to remotely characterize the lightning activity and the electrical environment within and around thunderstorms. ACES contributed important electrical and optical measurements not available from other sources. Also, the high altitude vantage point of the UAV observing platform (up to 55,000 feet) provided cloud-top perspective. By taking advantage of its slow flight speed (70 to 100 knots), long endurance, and high altitude flight, the Altus was flown near, and when possible, over (but never into) thunderstorms for long periods of time that allowed investigations to be conducted over entire storm life cycles. An innovative real time weather system was used to identify and vector the aircraft to selected thunderstorms and safely fly around these storms, while, at the same time monitor the weather near our base of operations. In addition, concurrent ground-based observations that included radar (Miami and Key West WSRBD, NASA NPOL), satellite imagery, and lightning (NALDN and Los Alamos EDOT) enable the UAV measurements to be more completely interpreted and evaluated in the context of the thunderstorm structure, evolution, and environment.

Emergency response to landslide using GNSS measurements and UAV

NASA Astrophysics Data System (ADS)

Nikolakopoulos, Konstantinos G.; Koukouvelas, Ioannis K.

2017-10-01

Landslide monitoring can be performed using many different methods: Classical geotechnical measurements like inclinometer, topographical survey measurements with total stations or GNSS sensors and photogrammetric techniques using airphotos or high resolution satellite images. However all these methods are expensive or difficult to be developed immediately after the landslide triggering. In contrast airborne technology and especially the use of Unmanned Aerial Vehicles (UAVs) make response to landslide disaster easier as UAVs can be launched quickly in dangerous terrains and send data about the sliding areas to responders on the ground either as RGB images or as videos. In addition, the emergency response to landslide is critical for the further monitoring. For proper displacement identification all the above mentioned monitoring methods need a high resolution and a very accurate representation of the relief. The ideal solution for the accurate and quick mapping of a landslide is the combined use of UAV's photogrammetry and GNSS measurements. UAVs have started their development as expensive toys but they currently became a very valuable tool in large scale mapping of sliding areas. The purpose of this work is to demonstrate an effective solution for the initial landslide mapping immediately after the occurrence of the phenomenon and the possibility of the periodical assessment of the landslide. Three different landslide cases from Greece are presented in the current study. All three landslides have different characteristics: occurred in different geomorphologic environments, triggered by different causes and had different geologic bedrock. In all three cases we performed detailed GNSS measurements of the landslide area, we generated orthophotos as well as Digital Surface Models (DSMs) at an accuracy of less than +/-10 cm. Slide direction and velocity, mass balances as well as protection and mitigation measurements can be derived from the application of the UAVs. Those data in addition are accurate, cost- and time-effective.

Observing Crop-Height Dynamics Using a UAV

NASA Astrophysics Data System (ADS)

Ziliani, M. G.; Parkes, S. D.; McCabe, M.

2017-12-01

Retrieval of vegetation height during a growing season is a key indicator for monitoring crop status, offering insight to the forecast yield relative to previous planting cycles. Improvement in Unmanned Aerial Vehicle (UAV) technologies, supported by advances in computer vision and photogrammetry software, has enabled retrieval of crop heights with much higher spatial resolution and coverage. These methodologies retrieve a Digital Surface Map (DSM), which combine terrain and crop elements to obtain a Crop Surface Map (CSM). Here we describe an automated method for deriving high resolution CSMs from a DSM, using RGB imagery from a UAV platform. Importantly, the approach does not require the need for a digital terrain map (DTM). The method involves distinguishing between vegetation and bare-ground cover pixels, using vegetation index maps from the RGB orthomosaic derived from the same flight as the DSM. We show that the absolute crop height can be extracted to within several centimeters, exploiting the data captured from a single UAV flight. In addition, the method is applied across five surveys during a maize growing cycle and compared against a terrain map constructed from a baseline UAV survey undertaken prior to crop growth. Results show that the approach is able to reproduce the observed spatial variability of the crop height within the maize field throughout the duration of the growing season. This is particularly valuable since it may be employed to detect intra-field problems (i.e. fertilizer variability, inefficiency in the irrigation system, salinity etc.) at different stages of the season, from which remedial action can be initiated to mitigate against yield loss. The method also demonstrates that UAV imagery combined with commercial photogrammetry software can determine a CSM from a single flight without the requirement of a prior DTM. This, together with the dynamic crop height estimation, provide useful information with which to inform precision agricultural management at the local scale.

On-board computational efficiency in real time UAV embedded terrain reconstruction

NASA Astrophysics Data System (ADS)

Partsinevelos, Panagiotis; Agadakos, Ioannis; Athanasiou, Vasilis; Papaefstathiou, Ioannis; Mertikas, Stylianos; Kyritsis, Sarantis; Tripolitsiotis, Achilles; Zervos, Panagiotis

2014-05-01

In the last few years, there is a surge of applications for object recognition, interpretation and mapping using unmanned aerial vehicles (UAV). Specifications in constructing those UAVs are highly diverse with contradictory characteristics including cost-efficiency, carrying weight, flight time, mapping precision, real time processing capabilities, etc. In this work, a hexacopter UAV is employed for near real time terrain mapping. The main challenge addressed is to retain a low cost flying platform with real time processing capabilities. The UAV weight limitation affecting the overall flight time, makes the selection of the on-board processing components particularly critical. On the other hand, surface reconstruction, as a computational demanding task, calls for a highly demanding processing unit on board. To merge these two contradicting aspects along with customized development, a System on a Chip (SoC) integrated circuit is proposed as a low-power, low-cost processor, which natively supports camera sensors and positioning and navigation systems. Modern SoCs, such as Omap3530 or Zynq, are classified as heterogeneous devices and provide a versatile platform, allowing access to both general purpose processors, such as the ARM11, as well as specialized processors, such as a digital signal processor and floating field-programmable gate array. A UAV equipped with the proposed embedded processors, allows on-board terrain reconstruction using stereo vision in near real time. Furthermore, according to the frame rate required, additional image processing may concurrently take place, such as image rectification andobject detection. Lastly, the onboard positioning and navigation (e.g., GNSS) chip may further improve the quality of the generated map. The resulting terrain maps are compared to ground truth geodetic measurements in order to access the accuracy limitations of the overall process. It is shown that with our proposed novel system,there is much potential in computational efficiency on board and in optimized time constraints.

A Multi-Disciplinary Approach to Remote Sensing through Low-Cost UAVs.

PubMed

Calvario, Gabriela; Sierra, Basilio; Alarcón, Teresa E; Hernandez, Carmen; Dalmau, Oscar

2017-06-16

The use of Unmanned Aerial Vehicles (UAVs) based on remote sensing has generated low cost monitoring, since the data can be acquired quickly and easily. This paper reports the experience related to agave crop analysis with a low cost UAV. The data were processed by traditional photogrammetric flow and data extraction techniques were applied to extract new layers and separate the agave plants from weeds and other elements of the environment. Our proposal combines elements of photogrammetry, computer vision, data mining, geomatics and computer science. This fusion leads to very interesting results in agave control. This paper aims to demonstrate the potential of UAV monitoring in agave crops and the importance of information processing with reliable data flow.

A Multi-Disciplinary Approach to Remote Sensing through Low-Cost UAVs

PubMed Central

Calvario, Gabriela; Sierra, Basilio; Alarcón, Teresa E.; Hernandez, Carmen; Dalmau, Oscar

2017-01-01

The use of Unmanned Aerial Vehicles (UAVs) based on remote sensing has generated low cost monitoring, since the data can be acquired quickly and easily. This paper reports the experience related to agave crop analysis with a low cost UAV. The data were processed by traditional photogrammetric flow and data extraction techniques were applied to extract new layers and separate the agave plants from weeds and other elements of the environment. Our proposal combines elements of photogrammetry, computer vision, data mining, geomatics and computer science. This fusion leads to very interesting results in agave control. This paper aims to demonstrate the potential of UAV monitoring in agave crops and the importance of information processing with reliable data flow. PMID:28621740

Use of the Aerosonde Unihabited Aerial Vehicle (UAV) in the Fourth Convection and Moisture Experiment (CAMEX 4)

NASA Technical Reports Server (NTRS)

Hipskind, R. Stephen; Curry, Judy; Holland, Greg

2001-01-01

The Fourth Convection and Moisture Experiment (CAMEX 4) was a scientific field experiment based in Florida in summer 2001 focused on the study of hurricanes off the east coast of the United States. Sponsored by the National Aeronautics and Space Administration's Office of Earth Science, and conducted in collaboration with the National Oceanic and Atmospheric Administration's annual hurricane research program, CAMEX 4 utilized aircraft, ground-based and satellite instrumentation to obtain unprecedented, three dimensional characterizations of these important storms. The Aerosonde UAV was selected by NASA to participate in CAMEX 4 because it provided a unique capability to obtain measurements in the atmospheric boundary layer in and around the storms, unattainable by other platforms or measurement capabilities. This talk focuses on the NASA review process that was followed to coordinate the UAV activity with the conventional aircraft operations, as well as with the other participating agencies and the FAA. We will discuss how Aerosonde addressed the issues of safety, coordination and communication and summarize the lessons learned.

Ubiquitous UAVs: a cloud based framework for storing, accessing and processing huge amount of video footage in an efficient way

NASA Astrophysics Data System (ADS)

Efstathiou, Nectarios; Skitsas, Michael; Psaroudakis, Chrysostomos; Koutras, Nikolaos

2017-09-01

Nowadays, video surveillance cameras are used for the protection and monitoring of a huge number of facilities worldwide. An important element in such surveillance systems is the use of aerial video streams originating from onboard sensors located on Unmanned Aerial Vehicles (UAVs). Video surveillance using UAVs represent a vast amount of video to be transmitted, stored, analyzed and visualized in a real-time way. As a result, the introduction and development of systems able to handle huge amount of data become a necessity. In this paper, a new approach for the collection, transmission and storage of aerial videos and metadata is introduced. The objective of this work is twofold. First, the integration of the appropriate equipment in order to capture and transmit real-time video including metadata (i.e. position coordinates, target) from the UAV to the ground and, second, the utilization of the ADITESS Versatile Media Content Management System (VMCMS-GE) for storing of the video stream and the appropriate metadata. Beyond the storage, VMCMS-GE provides other efficient management capabilities such as searching and processing of videos, along with video transcoding. For the evaluation and demonstration of the proposed framework we execute a use case where the surveillance of critical infrastructure and the detection of suspicious activities is performed. Collected video Transcodingis subject of this evaluation as well.

An Overview of Small Unmanned Aerial Vehicles for Air Quality Measurements: Present Applications and Future Prospectives

PubMed Central

Villa, Tommaso Francesco; Gonzalez, Felipe; Miljievic, Branka; Ristovski, Zoran D.; Morawska, Lidia

2016-01-01

Assessment of air quality has been traditionally conducted by ground based monitoring, and more recently by manned aircrafts and satellites. However, performing fast, comprehensive data collection near pollution sources is not always feasible due to the complexity of sites, moving sources or physical barriers. Small Unmanned Aerial Vehicles (UAVs) equipped with different sensors have been introduced for in-situ air quality monitoring, as they can offer new approaches and research opportunities in air pollution and emission monitoring, as well as for studying atmospheric trends, such as climate change, while ensuring urban and industrial air safety. The aims of this review were to: (1) compile information on the use of UAVs for air quality studies; and (2) assess their benefits and range of applications. An extensive literature review was conducted using three bibliographic databases (Scopus, Web of Knowledge, Google Scholar) and a total of 60 papers was found. This relatively small number of papers implies that the field is still in its early stages of development. We concluded that, while the potential of UAVs for air quality research has been established, several challenges still need to be addressed, including: the flight endurance, payload capacity, sensor dimensions/accuracy, and sensitivity. However, the challenges are not simply technological, in fact, policy and regulations, which differ between countries, represent the greatest challenge to facilitating the wider use of UAVs in atmospheric research. PMID:27420065

Optimal UAV Path Planning for Tracking a Moving Ground Vehicle with a Gimbaled Camera

DTIC Science & Technology

2014-03-27

micro SD card slot to record all video taken at 1080P resolution. This feature allows the team to record the high definition video taken by the...Inequality constraints 64 h=[]; %Equality constraints 104 Bibliography 1. “ DIY Drones: Official ArduPlane Repository”, 2013. URL https://code

Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation

PubMed Central

Gonzalez, Luis F.; Montes, Glen A.; Puig, Eduard; Johnson, Sandra; Mengersen, Kerrie; Gaston, Kevin J.

2016-01-01

Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification. PMID:26784196

Leaf Area Index Estimation in Vineyards from Uav Hyperspectral Data, 2d Image Mosaics and 3d Canopy Surface Models

NASA Astrophysics Data System (ADS)

Kalisperakis, I.; Stentoumis, Ch.; Grammatikopoulos, L.; Karantzalos, K.

2015-08-01

The indirect estimation of leaf area index (LAI) in large spatial scales is crucial for several environmental and agricultural applications. To this end, in this paper, we compare and evaluate LAI estimation in vineyards from different UAV imaging datasets. In particular, canopy levels were estimated from i.e., (i) hyperspectral data, (ii) 2D RGB orthophotomosaics and (iii) 3D crop surface models. The computed canopy levels have been used to establish relationships with the measured LAI (ground truth) from several vines in Nemea, Greece. The overall evaluation indicated that the estimated canopy levels were correlated (r2 > 73%) with the in-situ, ground truth LAI measurements. As expected the lowest correlations were derived from the calculated greenness levels from the 2D RGB orthomosaics. The highest correlation rates were established with the hyperspectral canopy greenness and the 3D canopy surface models. For the later the accurate detection of canopy, soil and other materials in between the vine rows is required. All approaches tend to overestimate LAI in cases with sparse, weak, unhealthy plants and canopy.

Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation.

PubMed

Gonzalez, Luis F; Montes, Glen A; Puig, Eduard; Johnson, Sandra; Mengersen, Kerrie; Gaston, Kevin J

2016-01-14

Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.

Advanced wireless mobile collaborative sensing network for tactical and strategic missions

NASA Astrophysics Data System (ADS)

Xu, Hao

2017-05-01

In this paper, an advanced wireless mobile collaborative sensing network will be developed. Through properly combining wireless sensor network, emerging mobile robots and multi-antenna sensing/communication techniques, we could demonstrate superiority of developed sensing network. To be concrete, heterogeneous mobile robots including unmanned aerial vehicle (UAV) and unmanned ground vehicle (UGV) are equipped with multi-model sensors and wireless transceiver antennas. Through real-time collaborative formation control, multiple mobile robots can team the best formation that can provide most accurate sensing results. Also, formatting multiple mobile robots can also construct a multiple-input multiple-output (MIMO) communication system that can provide a reliable and high performance communication network.

Armed and Dangerous? UAVs and U.S. Security

DTIC Science & Technology

2014-01-01

MEMS] as inertial navigation units [INUs]. This technology is widely used in commercial products, such as toy helicopters and Wii controllers. The...aircraft? In conclusion, both the MTCR and Wassenaar Arrange- ment provide the United States with the flexibility and controls to be able to balance its...security and nonproliferation goals with respect to armed UAVs. Perhaps more problematic is whether the government interagency can strike a balance

Optimization of dynamic soaring maneuvers to enhance endurance of a versatile UAV

NASA Astrophysics Data System (ADS)

Mir, Imran; Maqsood, Adnan; Akhtar, Suhail

2017-06-01

Dynamic soaring is a process of acquiring energy available in atmospheric wind shears and is commonly exhibited by soaring birds to perform long distance flights. This paper aims to demonstrate a viable algorithm which can be implemented in near real time environment to formulate optimal trajectories for dynamic soaring maneuvers for a small scale Unmanned Aerial Vehicle (UAV). The objective is to harness maximum energy from atmosphere wind shear to improve loiter time for Intelligence, Surveillance and Reconnaissance (ISR) missions. Three-dimensional point-mass UAV equations of motion and linear wind gradient profile are used to model flight dynamics. Utilizing UAV states, controls, operational constraints, initial and terminal conditions that enforce a periodic flight, dynamic soaring problem is formulated as an optimal control problem. Optimized trajectories of the maneuver are subsequently generated employing pseudo spectral techniques against distant UAV performance parameters. The discussion also encompasses the requirement for generation of optimal trajectories for dynamic soaring in real time environment and the ability of the proposed algorithm for speedy solution generation. Coupled with the fact that dynamic soaring is all about immediately utilizing the available energy from the wind shear encountered, the proposed algorithm promises its viability for practical on board implementations requiring computation of trajectories in near real time.

The Development Status and Key Technologies of Solar Powered Unmanned Air Vehicle

NASA Astrophysics Data System (ADS)

Sai, Li; Wei, Zhou; Xueren, Wang

2017-03-01

By analyzing the development status of several typical solar powered unmanned aerial vehicles (UAV) at home and abroad, the key technologies involved in the design and manufacture of solar powered UAV and the technical difficulties need to be solved at present are obtained. It is pointed out that with the improvement of energy system efficiency, advanced aerodynamic configuration design, realization of high applicability flight stability and control system, breakthrough of efficient propulsion system, the application prospect of solar powered UAV will be more extensive.

A LiDAR and IMU Integrated Indoor Navigation System for UAVs and Its Application in Real-Time Pipeline Classification

PubMed Central

Kumar, G. Ajay; Patil, Ashok Kumar; Patil, Rekha; Park, Seong Sill; Chai, Young Ho

2017-01-01

Mapping the environment of a vehicle and localizing a vehicle within that unknown environment are complex issues. Although many approaches based on various types of sensory inputs and computational concepts have been successfully utilized for ground robot localization, there is difficulty in localizing an unmanned aerial vehicle (UAV) due to variation in altitude and motion dynamics. This paper proposes a robust and efficient indoor mapping and localization solution for a UAV integrated with low-cost Light Detection and Ranging (LiDAR) and Inertial Measurement Unit (IMU) sensors. Considering the advantage of the typical geometric structure of indoor environments, the planar position of UAVs can be efficiently calculated from a point-to-point scan matching algorithm using measurements from a horizontally scanning primary LiDAR. The altitude of the UAV with respect to the floor can be estimated accurately using a vertically scanning secondary LiDAR scanner, which is mounted orthogonally to the primary LiDAR. Furthermore, a Kalman filter is used to derive the 3D position by fusing primary and secondary LiDAR data. Additionally, this work presents a novel method for its application in the real-time classification of a pipeline in an indoor map by integrating the proposed navigation approach. Classification of the pipeline is based on the pipe radius estimation considering the region of interest (ROI) and the typical angle. The ROI is selected by finding the nearest neighbors of the selected seed point in the pipeline point cloud, and the typical angle is estimated with the directional histogram. Experimental results are provided to determine the feasibility of the proposed navigation system and its integration with real-time application in industrial plant engineering. PMID:28574474

ALTUS Cumulus Electrification Study (ACES)

NASA Technical Reports Server (NTRS)

Kim, Tony; Blakeslee, Richard; Russell, Larry W. (Technical Monitor)

2002-01-01

The ALTUS Cumulus Electrification Study (ACES) is an uninhabited aerial vehicle (UAV)-based project that will investigate thunderstorms in the vicinity of the Florida Everglades in August 2002. ACES is being conducted to both investigate storm electrical activity and its relationship to storm morphology, and validate Tropical Rainfall Measurement Mission (TRMM) satellite measurements. In addition, as part of NASA's UAV-based science demonstration program, this project will provide a scientifically useful demonstration of the utility and promise of UAV platforms for Earth science and applications observations. Part of the demonstration involves getting approvals from the Federal Aviation Administration and the NASA airworthiness flight safety review board. ACES will employ the ALTUS II aircraft, built by General Atomics - Aeronautical Systems, Inc. Key science objectives simultaneously addressed by ACES are to: (1) investigate lightning-storm relationships, (2) study storm electrical budgets, and (3) provide Lightning Imaging Sensor validation. The ACES payload, already developed and flown on ALTUS, includes electrical, magnetic, and optical sensors to remotely characterize the lightning activity and the electrical environment within and around thunderstorms. ACES will contribute important electrical and optical measurements not available from other sources. Also, the high altitude vantage point of the UAV observing platform (up to 55,000 feet) offers a useful 'cloud-top' perspective. By taking advantage of its slow flight speed (70 to 100 knots), long endurance, and high altitude flight, the ALTUS will be flown near, and when possible, above (but never into) thunderstorms for long periods of time, allowing investigations to be conducted over entire storm life cycles. In addition, concurrent ground-based observations will enable the UAV measurements to be more completely interpreted and evaluated in the context of the thunderstorm structure, evolution, and environment.

Critical Zone Co-dynamics: Quantifying Interactions between Subsurface, Land Surface, and Vegetation Properties Using UAV and Geophysical Approaches

NASA Astrophysics Data System (ADS)

Dafflon, B.; Leger, E.; Peterson, J.; Falco, N.; Wainwright, H. M.; Wu, Y.; Tran, A. P.; Brodie, E.; Williams, K. H.; Versteeg, R.; Hubbard, S. S.

2017-12-01

Improving understanding and modelling of terrestrial systems requires advances in measuring and quantifying interactions among subsurface, land surface and vegetation processes over relevant spatiotemporal scales. Such advances are important to quantify natural and managed ecosystem behaviors, as well as to predict how watershed systems respond to increasingly frequent hydrological perturbations, such as droughts, floods and early snowmelt. Our study focuses on the joint use of UAV-based multi-spectral aerial imaging, ground-based geophysical tomographic monitoring (incl., electrical and electromagnetic imaging) and point-scale sensing (soil moisture sensors and soil sampling) to quantify interactions between above and below ground compartments of the East River Watershed in the Upper Colorado River Basin. We evaluate linkages between physical properties (incl. soil composition, soil electrical conductivity, soil water content), metrics extracted from digital surface and terrain elevation models (incl., slope, wetness index) and vegetation properties (incl., greenness, plant type) in a 500 x 500 m hillslope-floodplain subsystem of the watershed. Data integration and analysis is supported by numerical approaches that simulate the control of soil and geomorphic characteristic on hydrological processes. Results provide an unprecedented window into critical zone interactions, revealing significant below- and above-ground co-dynamics. Baseline geophysical datasets provide lithological structure along the hillslope, which includes a surface soil horizon, underlain by a saprolite layer and the fractured Mancos shale. Time-lapse geophysical data show very different moisture dynamics in various compartments and locations during the winter and growing season. Integration with aerial imaging reveals a significant linkage between plant growth and the subsurface wetness, soil characteristics and the topographic gradient. The obtained information about the organization and connectivity of the landscape is being transferred to larger regions using aerial imaging and will be used to constrain multi-scale, multi-physics hydro-biogeochemical simulations of the East River watershed response to hydrological perturbations.

MosquitoNet: investigating the use of UAV and artificial neural networks for integrated mosquito management

NASA Astrophysics Data System (ADS)

Case, E.; Ren, Y.; Shragai, T.; Erickson, D.

2017-12-01

Integrated mosquito control is expensive and resource intensive, and changing climatic factors are predicted to expand the habitable range of disease-carrying mosquitoes into new regions in the United States. Of particular concern in the northeastern United States are aedes albopictus, an aggressive, invasive species of mosquito that can transmit both native and exotic disease. Ae. albopictus prefer to live near human populations and breed in artificial containers with as little as two millimeters of standing water, exponentially increasing the difficulty of source control in suburban and urban areas. However, low-cost unmanned aerial vehicles (UAVs) can be used to photograph large regions at centimeter-resolution, and can image containers of interest in suburban neighborhoods. While proofs-of-concepts have been shown using UAVs to identify naturally occurring bodies of water, they have not been used to identify mosquito habitat in more populated areas. One of the primary challenges is that post-processing high-resolution aerial imagery is still time intensive, often labelled by hand or with programs built for satellite imagery. Artificial neural networks have been highly successful at image recognition tasks; in the past five years, convolutional neural networks (CNN) have surpassed or aided trained humans in identification of skin cancer, agricultural crops, and poverty levels from satellite imagery. MosquitoNet, a dual classifier built from the Single Shot Multibox Detector and VGG16 architectures, was trained on UAV­­­­­ aerial imagery taken during a larval study in Westchester County in southern New York State in July and August 2017. MosquitoNet was designed to assess the habitat risk of suburban properties by automating the identification and counting of containers like tires, toys, garbage bins, flower pots, etc. The SSD-based architecture marked small containers and other habitat indicators while the VGG16-based architecture classified the type of container and presence of water. These were then mapped, and risk of breeding ground o­­­n a given property assessed. These methods could significantly increase the ability of vector control agencies to contain mosquito populat­­ions.

Semiautonomous Avionics-and-Sensors System for a UAV

NASA Technical Reports Server (NTRS)

Shams, Qamar

2006-01-01

Unmanned Aerial Vehicles (UAVs) autonomous or remotely controlled pilotless aircraft have been recently thrust into the spotlight for military applications, for homeland security, and as test beds for research. In addition to these functions, there are many space applications in which lightweight, inexpensive, small UAVS can be used e.g., to determine the chemical composition and other qualities of the atmospheres of remote planets. Moreover, on Earth, such UAVs can be used to obtain information about weather in various regions; in particular, they can be used to analyze wide-band acoustic signals to aid in determining the complex dynamics of movement of hurricanes. The Advanced Sensors and Electronics group at Langley Research Center has developed an inexpensive, small, integrated avionics-and-sensors system to be installed in a UAV that serves two purposes. The first purpose is to provide flight data to an AI (Artificial Intelligence) controller as part of an autonomous flight-control system. The second purpose is to store data from a subsystem of distributed MEMS (microelectromechanical systems) sensors. Examples of these MEMS sensors include humidity, temperature, and acoustic sensors, plus chemical sensors for detecting various vapors and other gases in the environment. The critical sensors used for flight control are a differential- pressure sensor that is part of an apparatus for determining airspeed, an absolute-pressure sensor for determining altitude, three orthogonal accelerometers for determining tilt and acceleration, and three orthogonal angular-rate detectors (gyroscopes). By using these eight sensors, it is possible to determine the orientation, height, speed, and rates of roll, pitch, and yaw of the UAV. This avionics-and-sensors system is shown in the figure. During the last few years, there has been rapid growth and advancement in the technological disciplines of MEMS, of onboard artificial-intelligence systems, and of smaller, faster, and smarter wireless telemetry systems. The major attraction of MEMS lies in orders-of-magnitude reductions of power requirements relative to traditional electronic components that perform equivalent functions. In addition, the compactness of MEMS, relative to functionally equivalent traditional electronics systems, makes MEMS attractive for UAV applications. Recent advances in MEMS have made it possible to produce pressure, acceleration, humidity, and temperature sensors having masses in subgram range and possessing sensitivities and accuracies comparable to those of larger devices.

On parallel hybrid-electric propulsion system for unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Hung, J. Y.; Gonzalez, L. F.

2012-05-01

This paper presents a review of existing and current developments and the analysis of Hybrid-Electric Propulsion Systems (HEPS) for small fixed-wing Unmanned Aerial Vehicles (UAVs). Efficient energy utilisation on an UAV is essential to its functioning, often to achieve the operational goals of range, endurance and other specific mission requirements. Due to the limitations of the space available and the mass budget on the UAV, it is often a delicate balance between the onboard energy available (i.e. fuel) and achieving the operational goals. One technology with potential in this area is with the use of HEPS. In this paper, information on the state-of-art technology in this field of research is provided. A description and simulation of a parallel HEPS for a small fixed-wing UAV by incorporating an Ideal Operating Line (IOL) control strategy is described. Simulation models of the components in a HEPS were designed in the MATLAB Simulink environment. An IOL analysis of an UAV piston engine was used to determine the most efficient points of operation for this engine. The results show that an UAV equipped with this HEPS configuration is capable of achieving a fuel saving of 6.5%, compared to the engine-only configuration.

Active-Twist Rotor Control Applications for UAVs

NASA Technical Reports Server (NTRS)

Wilbur, Matthew L.; Wilkie, W. Keats

2004-01-01

The current state-of-the-art in active-twist rotor control is discussed using representative examples from analytical and experimental studies, and the application to rotary-wing UAVs is considered. Topics include vibration and noise reduction, rotor performance improvement, active blade tracking, stability augmentation, and rotor blade de-icing. A review of the current status of piezoelectric fiber composite actuator technology, the class of piezoelectric actuators implemented in active-twist rotor systems, is included.

Investigation of a robust tendon-sheath mechanism for flexible membrane wing application in mini-UAV

NASA Astrophysics Data System (ADS)

Lee, Shian; Tjahjowidodo, Tegoeh; Lee, Hsuchew; Lai, Benedict

2017-02-01

Two inherent issues manifest themselves in flying mini-unmanned aerial vehicles (mini-UAV) in the dense area at tropical climate regions, namely disturbances from gusty winds and limited space for deployment tasks. Flexible membrane wing (FMW) UAVs are seen to be potentials to mitigate these problems. FMWs are adaptable to gusty airflow as the wings are able to flex according to the gust load to reduce the effective angle-of-attack, thus, reducing the aerodynamic loads on the wing. On the other hand, the flexible structure is allowing the UAV to fold in a compact package, and later on, the mini-UAV can be deployed instantly from the storage tube, e.g. through a catapult mechanism. This paper discusses the development of an FMW UAV actuated by a tendon-sheath mechanism (TSM). This approach allows the wing to morph to generate a rolling moment, while still allowing the wing to fold. Dynamic characteristics of the mechanism that exhibits the strong nonlinear phenomenon of friction on TSM are modeled and compensated for. A feed-forward controller was implemented based on the identified nonlinear behavior to control the warping position of the wing. The proposed strategy is validated experimentally in a wind tunnel facility by creating a gusty environment that is imitating a realistic gusty condition based upon the results of computational fluid dynamics (CFD) simulation. The results demonstrate a stable and robust wing-warping actuation, even in gusty conditions. Accurate wing-warping can be achieved via the TSM, while also allowing the wings to fold.

Advanced Broadband Links for TIER III UAV Data Communication

NASA Astrophysics Data System (ADS)

Griethe, Wolfgang; Gregory, Mark; Heine, Frank; Kampfner, Hartmut

2011-08-01

Unmanned Aeronautical Vehicle (UAV) are getting more and more importance because of their prominent role as national reconnaissance systems, for disaster monitoring, and environmental mapping. However, the existence of reliable and robust data links are indispensable for Unmanned Aircraft System (UAS) missions. In particular for Beyond Line-Of-Sight operations (BLOS) of Tier III UAVs, satellite data links are a key element since extensive sensor data have to be transmitted preferably in real-time or near real-time.The paper demonstrates that the continuously increasing number of UAS and the intensified use of high resolution sensors will reveal RF-bandwidth as a limitating factor in the communication chain of Tier III UAVs. The RF-bandwidth gap can be partly closed by use of high-order modulation, of course, but much more progress in terms of bandwidth allocation can be achieved by using optical transmission technology. Consequently, the paper underlines that meanwhile this technology has been sufficiently verified in space, and shows that optical links are suited as well for broadband communications of Tier III UAVs. Moreover, the advantages of LaserCom in UAV scenarios and its importance for Network Centric Warfare (NCW) as well as for Command, Control, Communications, Computers, Intelligens, Surveillance, and Reconnaissance (C4ISR) are emphasized. Numerous practical topics and design requirements, relevant for the establishment of optical links onboard of Tier III UAVs, are discussed.

Annual low-cost monitoring of a coastal site in Greece by an unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Hoffmeister, Dirk; Bareth, Georg

2016-04-01

Coastal areas are under permanent change and are also the result of past processes. These processes are for example sediment transport, accumulation and erosion by normal and extreme waves (storms or tsunamis). As about 23% of the World's population lives within a 100 km distance of coasts, knowledge about coastal processes is important, in particular for possible changes in the nearby future. The past devastating tsunami events demonstrated profoundly the high vulnerability of coastal areas. In order to estimate the different effects, coastal monitoring approaches are of interest. Several different methods exist in order to determine changes in the sedimentary budget and coastline configuration. In order to estimate constant annual changes, we have applied terrestrial laser scanning (TLS) in an annual monitoring approach (2009-2011). In 2014, we changed to an approach based on dense imaging and structure-from-motion, applying an unmanned aerial vehicle (UAV) in order to conduct an annual monitoring of a coastal site in western Greece. Therefore, a GoPro Hero 3+ and a Canon PowerShot S110 mounted on a DJI-Phantom 2 were used. All surveys were conducted in a manually structured image acquisition with a huge overlap. Ground control points (GCP) were measured by tachymetric surveying. This successful approach was repeated again in 2015 with the Canon camera. The measurements of 2014 were controlled by an additional TLS survey, which revealed the high accuracy and more suitable coverage for the UAV-based data. Likewise, the large picture datasets were artificially reduced in order to estimate the most efficient number of images for dense point cloud processing. In addition, also the number of GCPs was decreased for one dataset. Overall, high-resolution digital elevation models with a ground resolution of 10 mm and an equal accuracy were achieved with this low-cost equipment. The data reveals the slight changes on this selected site.

Utilizing the Iterative Closest Point (ICP) algorithm for enhanced registration of high resolution surface models - more than a simple black-box application

NASA Astrophysics Data System (ADS)

Stöcker, Claudia; Eltner, Anette

2016-04-01

Advances in computer vision and digital photogrammetry (i.e. structure from motion) allow for fast and flexible high resolution data supply. Within geoscience applications and especially in the field of small surface topography, high resolution digital terrain models and dense 3D point clouds are valuable data sources to capture actual states as well as for multi-temporal studies. However, there are still some limitations regarding robust registration and accuracy demands (e.g. systematic positional errors) which impede the comparison and/or combination of multi-sensor data products. Therefore, post-processing of 3D point clouds can heavily enhance data quality. In this matter the Iterative Closest Point (ICP) algorithm represents an alignment tool which iteratively minimizes distances of corresponding points within two datasets. Even though tool is widely used; it is often applied as a black-box application within 3D data post-processing for surface reconstruction. Aiming for precise and accurate combination of multi-sensor data sets, this study looks closely at different variants of the ICP algorithm including sub-steps of point selection, point matching, weighting, rejection, error metric and minimization. Therefore, an agricultural utilized field was investigated simultaneously by terrestrial laser scanning (TLS) and unmanned aerial vehicle (UAV) sensors two times (once covered with sparse vegetation and once bare soil). Due to different perspectives both data sets show diverse consistency in terms of shadowed areas and thus gaps so that data merging would provide consistent surface reconstruction. Although photogrammetric processing already included sub-cm accurate ground control surveys, UAV point cloud exhibits an offset towards TLS point cloud. In order to achieve the transformation matrix for fine registration of UAV point clouds, different ICP variants were tested. Statistical analyses of the results show that final success of registration and therefore data quality depends particularly on parameterization and choice of error metric, especially for erroneous data sets as in the case of sparse vegetation cover. At this, the point-to-point metric is more sensitive to data "noise" than the point-to-plane metric which results in considerably higher cloud-to-cloud distances. Concluding, in order to comply with accuracy demands of high resolution surface reconstruction and the aspect that ground control surveys can reach their limits both in time exposure and terrain accessibility ICP algorithm represents a great tool to refine rough initial alignment. Here different variants of registration modules allow for individual application according to the quality of the input data.

Development of the Global Ozone Lidar Demonstrator (GOLD) Instrument for Deployment on the NASA Global Hawk

NASA Technical Reports Server (NTRS)

Hair, Jonathan W.; Browell, Edward V.; McGee, Thomas; Butler, Carolyn; Fenn, Marta; Os,ao (. Sued); Notari, Anthony; Collins, James; Cleckner, Craig; Hostetler, Chris

2010-01-01

A compact ozone (O3) and aerosol lidar system is being developed for conducting global atmospheric investigations from the NASA Global Hawk Uninhabited Aerial Vehicle (UAV) and for enabling the development and test of a space-based O3 and aerosol lidar. GOLD incorporates advanced technologies and designs to produce a compact, autonomously operating O3 and aerosol Differential Absorption Lidar (DIAL) system for a UAV platform. The GOLD system leverages advanced Nd:YAG and optical parametric oscillator laser technologies and receiver optics, detectors, and electronics. Significant progress has been made toward the development of the GOLD system, and this paper describes the objectives of this program, basic design of the GOLD system, and results from initial ground-based atmospheric tests.

A High-Throughput Processor for Flight Control Research Using Small UAVs

NASA Technical Reports Server (NTRS)

Klenke, Robert H.; Sleeman, W. C., IV; Motter, Mark A.

2006-01-01

There are numerous autopilot systems that are commercially available for small (<100 lbs) UAVs. However, they all share several key disadvantages for conducting aerodynamic research, chief amongst which is the fact that most utilize older, slower, 8- or 16-bit microcontroller technologies. This paper describes the development and testing of a flight control system (FCS) for small UAV s based on a modern, high throughput, embedded processor. In addition, this FCS platform contains user-configurable hardware resources in the form of a Field Programmable Gate Array (FPGA) that can be used to implement custom, application-specific hardware. This hardware can be used to off-load routine tasks such as sensor data collection, from the FCS processor thereby further increasing the computational throughput of the system.

Cooperative Control of UAVs for Localization of Intermittently Emitting Mobile Targets

DTIC Science & Technology

2009-08-01

as lawn - mower serpentine patterns [21]. Second, due to the limited energy supplies intrinsic to UAV applications, it is also important that the search...Robotic Embedded Systems Laboratory, Univ. Southern Calif., Los Angeles, CA, 2002. Tech. Rep. [21] J. Ousingsawat and M. G. Earl, “Modified lawn - mower search

A Cloud Robotics Based Service for Managing RPAS in Emergency, Rescue and Hazardous Scenarios

NASA Astrophysics Data System (ADS)

Silvagni, Mario; Chiaberge, Marcello; Sanguedolce, Claudio; Dara, Gianluca

2016-04-01

Cloud robotics and cloud services are revolutionizing not only the ICT world but also the robotics industry, giving robots more computing capabilities, storage and connection bandwidth while opening new scenarios that blend the physical to the digital world. In this vision, new IT architectures are required to manage robots, retrieve data from them and create services to interact with users. Among all the robots this work is mainly focused on flying robots, better known as drones, UAV (Unmanned Aerial Vehicle) or RPAS (Remotely Piloted Aircraft Systems). The cloud robotics approach shifts the concept of having a single local "intelligence" for every single UAV, as a unique device that carries out onboard all the computation and storage processes, to a more powerful "centralized brain" located in the cloud. This breakthrough opens new scenarios where UAVs are agents, relying on remote servers for most of their computational load and data storage, creating a network of devices where they can share knowledge and information. Many applications, using UAVs, are growing as interesting and suitable devices for environment monitoring. Many services can be build fetching data from UAVs, such as telemetry, video streaming, pictures or sensors data; once. These services, part of the IT architecture, can be accessed via web by other devices or shared with other UAVs. As test cases of the proposed architecture, two examples are reported. In the first one a search and rescue or emergency management, where UAVs are required for monitoring intervention, is shown. In case of emergency or aggression, the user requests the emergency service from the IT architecture, providing GPS coordinates and an identification number. The IT architecture uses a UAV (choosing among the available one according to distance, service status, etc.) to reach him/her for monitoring and support operations. In the meantime, an officer will use the service to see the current position of the UAV, its telemetry and video streaming from its camera. Data are stored for further use and documentation and can be shared to all the involved personal or services. The second case refer to imaging survey. An investigation area is selected using a map or a set of coordinates by a user that can be on the field on in a management facility. The cloud system elaborate this data and automatically compute a flight plan that consider the survey data requirements (i.e: picture ground resolution, overlapping) but also several environment constraints (i.e: no fly zones, possible hazardous areas, known obstacles, etc). Once the flight plan is loaded in the selected UAV the mission starts. During the mission, if a suitable data network coverage is available, the UAV transmit acquired images (typically low quality image to limit bandwidth) and shooting pose in order to perform a preliminary check during the mission and minimize failing in survey; if not, all data are uploaded asynchronously after the mission. The cloud servers perform all the tasks related to image processing (mosaic, ortho-photo, geo-referencing, 3D models) and data management.

Evaluation of composite materials providing improved acoustic transmission loss for UAVs

NASA Astrophysics Data System (ADS)

Callicoat, Jeffrey R.

With the proliferation of Unmanned Aerial Vehicles (UAVs) in civilian airspace in the near future, community noise will be a major issue of concern. Numerous studies have shown a direct link between community noise pollution (i.e., road traffic noise and airport noise) and serious health problems. There exists, therefore, a pressing need to create quiet UAVs, and this drives the need for noise-attenuating materials and structures suitable for UAV airframe fabrication. By shrouding predominant noise sources such as the engine, exhaust, and even the propeller (in the case of a ducted fan) with the airframe structure, the airframe can serve as a noise transmission barrier and substantially reduce UAV noise profiles. The present research effort is an experimental investigation of light-weight fiber-reinforced composite materials to provide high acoustic transmission loss (TL) for use in fabricating UAV airframes. A transmission loss tube acoustic test system was designed, fabricated, and validated, and extensive testing was done on numerous composite layups of interest for UAV fabrication. Composites under study included carbon fiber, fiberglass, and Kevlar fabrics as skin materials along with vinyl foam, Nomex honeycomb, and balsawood as core materials. Results from testing small 3"x3" samples in the TL tube led to the selection of four composite sandwich panels of interest for further study. Larger 36"x36" test samples of these selected layups were then fabricated and tested using a 2-room methodology. Whereas the TL tube yielded results in the stiffness-controlled region of acoustic behavior, the 2-room tests produced results in the mass-controlled region for these materials, enabling relative performance comparisons over both acoustic regimes. Recognizing that a good material for airframe fabrication should possess not only high TL, but also low weight and high stiffness, load-deflection tests were conducted and overall material performance was compared in terms of the parameter [(TL * stiffness) / surface density]. A sandwich panel layup of 5.7 oz carbon fiber skins with a vinyl foam core emerged as the preferable material choice, and a UAV fuselage of this construction was evaluated in the OSU anechoic chamber and shown to substantially reduce sound propagation from enclosed noise sources.

State estimation for autonomous flight in cluttered environments

NASA Astrophysics Data System (ADS)

Langelaan, Jacob Willem

Safe, autonomous operation in complex, cluttered environments is a critical challenge facing autonomous mobile systems. The research described in this dissertation was motivated by a particularly difficult example of autonomous mobility: flight of a small Unmanned Aerial Vehicle (UAV) through a forest. In cluttered environments (such as forests or natural and urban canyons) signals from navigation beacons such as GPS may frequently be occluded. Direct measurements of vehicle position are therefore unavailable, and information required for flight control, obstacle avoidance, and navigation must be obtained using only on-board sensors. However, payload limitations of small UAVs restrict both the mass and physical dimensions of sensors that can be carried. This dissertation describes the development and proof-of-concept demonstration of a navigation system that uses only a low-cost inertial measurement unit and a monocular camera. Micro electromechanical inertial measurements units are well suited to small UAV applications and provide measurements of acceleration and angular rate. However, they do not provide information about nearby obstacles (needed for collision avoidance) and their noise and bias characteristics lead to unbounded growth in computed position. A monocular camera can provide bearings to nearby obstacles and landmarks. These bearings can be used both to enable obstacle avoidance and to aid navigation. Presented here is a solution to the problem of estimating vehicle state (position, orientation and velocity) as well as positions of obstacles in the environment using only inertial measurements and bearings to obstacles. This is a highly nonlinear estimation problem, and standard estimation techniques such as the Extended Kalman Filter are prone to divergence in this application. In this dissertation a Sigma Point Kalman Filter is implemented, resulting in an estimator which is able to cope with the significant nonlinearities in the system equations and uncertainty in state estimates while remaining tractable for real-time operation. In addition, the issues of data association and landmark initialization are addressed. Estimator performance is examined through Monte Carlo simulations in both two and three dimensions for scenarios involving UAV flight in cluttered environments. Hardware tests and simulations demonstrate navigation through an obstacle-strewn environment by a small Unmanned Ground Vehicle.

UAV, DGPS, and Laser Transit Mapping of Microbial Mat Ecosystems on Little Ambergris Cay, B.W.I.

NASA Astrophysics Data System (ADS)

Stein, N.; Quinn, D. P.; Grotzinger, J. P.; Fischer, W. W.; Knoll, A. H.; Cantine, M.; Gomes, M. L.; Grotzinger, H. M.; Lingappa, U.; Metcalfe, K.; O'Reilly, S. S.; Orzechowski, E. A.; Riedman, L. A.; Strauss, J. V.; Trower, L.

2016-12-01

Little Ambergris Cay is a 6 km long, 1.6 km wide uninhabited island on the Caicos platform in the Turks and Caicos. Little Ambergris provides an analog for the study of microbial mat development in the sedimentary record. Recent field mapping during July of 2016 used UAV- and satellite-based images, differential GPS (DGPS), and total station theodolite (TST) measurements to characterize sedimentology and biofacies across the entirety of Little Ambergris Cay. Nine facies were identified in-situ during DGPS island transects including oolitic grainstone bedrock, sand flats, cutbank and mat-filled channels, hardground-lined bays with EPS-rich mat particles, mangroves, EPS mats, polygonal mats, and mats with blistered surface texture. These facies were mapped onto a 15 cm/pixel visible light orthomosaic of the island generated from more than 1500 nadir images taken by a UAV at 350 m standoff distance. A corresponding stereogrammetric digital elevation map was generated from drone images and 910 DGPS measurements acquired during several island transects. More than 1000 TST measurements provide additional facies elevation constraints, control points for satellite-based water depth calculations, and means to cross-calibrate and reconstruct the topographic profile of bedrock exposed at the beach. Additionally, the thickness of the underlying Holocene sediment fill was estimated over several island transects using a depth probe. Sub-cm resolution drone-based orthophotos of microbial mats were used to quantify polygonal mat size and textures. The mapping results highlight that sedimentary and bio-facies (including mat morphology and fabrics) correlate strongly with elevation. Notably, mat morphology was observed to be highly sensitive to cm-scale variations in topography and water depth. The productivity metric NDVI was computed for mat and vegetation facies using nadir images from a UAV-mounted two-band red-NIR camera. In combination with in situ facies mapping, these measurements provided ground truth for reduction of multispectral Landsat and Worldview-2 satellite images to evaluate mat distribution and diversity across a range of spatial and spectral facies variations.

Automatic detection of blurred images in UAV image sets

NASA Astrophysics Data System (ADS)

Sieberth, Till; Wackrow, Rene; Chandler, Jim H.

2016-12-01

Unmanned aerial vehicles (UAV) have become an interesting and active research topic for photogrammetry. Current research is based on images acquired by an UAV, which have a high ground resolution and good spectral and radiometrical resolution, due to the low flight altitudes combined with a high resolution camera. UAV image flights are also cost effective and have become attractive for many applications including, change detection in small scale areas. One of the main problems preventing full automation of data processing of UAV imagery is the degradation effect of blur caused by camera movement during image acquisition. This can be caused by the normal flight movement of the UAV as well as strong winds, turbulence or sudden operator inputs. This blur disturbs the visual analysis and interpretation of the data, causes errors and can degrade the accuracy in automatic photogrammetric processing algorithms. The detection and removal of these images is currently achieved manually, which is both time consuming and prone to error, particularly for large image-sets. To increase the quality of data processing an automated process is necessary, which must be both reliable and quick. This paper describes the development of an automatic filtering process, which is based upon the quantification of blur in an image. Images with known blur are processed digitally to determine a quantifiable measure of image blur. The algorithm is required to process UAV images fast and reliably to relieve the operator from detecting blurred images manually. The newly developed method makes it possible to detect blur caused by linear camera displacement and is based on human detection of blur. Humans detect blurred images best by comparing it to other images in order to establish whether an image is blurred or not. The developed algorithm simulates this procedure by creating an image for comparison using image processing. Creating internally a comparable image makes the method independent of additional images. However, the calculated blur value named SIEDS (saturation image edge difference standard-deviation) on its own does not provide an absolute number to judge if an image is blurred or not. To achieve a reliable judgement of image sharpness the SIEDS value has to be compared to other SIEDS values from the same dataset. The speed and reliability of the method was tested using a range of different UAV datasets. Two datasets will be presented in this paper to demonstrate the effectiveness of the algorithm. The algorithm proves to be fast and the returned values are optically correct, making the algorithm applicable for UAV datasets. Additionally, a close range dataset was processed to determine whether the method is also useful for close range applications. The results show that the method is also reliable for close range images, which significantly extends the field of application for the algorithm.

Comparing terrestrial laser scanning with ground and UAV-based imaging for national-level assessment of upland soil erosion

NASA Astrophysics Data System (ADS)

McShane, Gareth; Farrow, Luke; Morgan, David; Glendell, Miriam; James, Mike; Quinton, John; Evans, Martin; Anderson, Karen; Rawlins, Barry; Quine, Timothy; Debell, Leon; Benaud, Pia; Jones, Lee; Kirkham, Matthew; Lark, Murray; Rickson, Jane; Brazier, Richard

2015-04-01

Quantifying soil loss through erosion processes at a high resolution can be a time consuming and costly undertaking. In this pilot study 'a cost effective framework for monitoring soil erosion in England and Wales', funded by the UK Department for Environment, Food and Rural Affairs (Defra), we compare methods for collecting suitable topographic measurements via remote sensing. The aim is to enable efficient but detailed site-scale studies of erosion forms in inaccessible UK upland environments, to quantify dynamic processes, such as erosion and mass movement. The techniques assessed are terrestrial laser scanning (TLS), and unmanned aerial vehicle (UAV) photography and ground-based photography, both processed using structure-from-motion (SfM) 3D reconstruction software. Compared to other established techniques, such as expensive TLS, SfM offers a potentially low-cost alternative for the reconstruction of 3D high-resolution micro-topographic models from photographs taken with consumer grade cameras. However, whilst an increasing number of research papers examine the relative merits of these novel versus more established survey techniques, no study to date has compared both ground-based and aerial SfM photogrammetry with TLS scanning across a range of scales (from m2 to 16ha). The evaluation of these novel low cost techniques is particularly relevant in upland landscapes, where the remoteness and inaccessibility of field sites may render some of the more established survey techniques impractical. Volumetric estimates of soil loss are quantified using the digital surface models (DSMs) derived from the data from each technique and subtracted from a modelled pre-erosion surface. The results from each technique are compared. The UAV was able to capture information over a wide area, a range of altitudes and angles over the study area. Combined with automated SfM-based processing, this technique was able to produce rapid orthophotos to support ground-based data acquisition, as well as a DSM for volume loss measurement in larger features. However, the DSM of erosion features lacked the detail of those captured using the ground-based methods. Terrestrial laser scanning provided detailed, accurate, high density measurements of the ground surface over long (100s m) distances, but size and weight of the instrument made it difficult to use in mountainous environments. In addition, deriving a reliable bare-earth digital terrain model (DTM) from TLS was at times problematic due to the presence of tall shrubby vegetation. Ground-based photography produced comparable data sets to terrestrial laser scanning and was the most useful for characterising small and difficult to view features. The relative advantages, limitations and cost-effectiveness of each approach at 5 upland sites across the UK are discussed.

Real-time Collision Avoidance and Path Optimizer for Semi-autonomous UAVs.

NASA Astrophysics Data System (ADS)

Hawary, A. F.; Razak, N. A.

2018-05-01

Whilst UAV offers a potentially cheaper and more localized observation platform than current satellite or land-based approaches, it requires an advance path planner to reveal its true potential, particularly in real-time missions. Manual control by human will have limited line-of-sights and prone to errors due to careless and fatigue. A good alternative solution is to equip the UAV with semi-autonomous capabilities that able to navigate via a pre-planned route in real-time fashion. In this paper, we propose an easy-and-practical path optimizer based on the classical Travelling Salesman Problem and adopts a brute force search method to re-optimize the route in the event of collisions using range finder sensor. The former utilizes a Simple Genetic Algorithm and the latter uses Nearest Neighbour algorithm. Both algorithms are combined to optimize the route and avoid collision at once. Although many researchers proposed various path planning algorithms, we find that it is difficult to integrate on a basic UAV model and often lacks of real-time collision detection optimizer. Therefore, we explore a practical benefit from this approach using on-board Arduino and Ardupilot controllers by manually emulating the motion of an actual UAV model prior to test on the flying site. The result showed that the range finder sensor provides a real-time data to the algorithm to find a collision-free path and eventually optimized the route successfully.

The Performance Analysis of a Uav Based Mobile Mapping System Platform

NASA Astrophysics Data System (ADS)

Tsai, M. L.; Chiang, K. W.; Lo, C. F.; Ch, C. H.

2013-08-01

To facilitate applications such as environment detection or disaster monitoring, the development of rapid low cost systems for collecting near real-time spatial information is very critical. Rapid spatial information collection has become an emerging trend for remote sensing and mapping applications. This study develops a Direct Georeferencing (DG) based fixed-wing Unmanned Aerial Vehicle (UAV) photogrammetric platform where an Inertial Navigation System (INS)/Global Positioning System (GPS) integrated Positioning and Orientation System (POS) system is implemented to provide the DG capability of the platform. The performance verification indicates that the proposed platform can capture aerial images successfully. A flight test is performed to verify the positioning accuracy in DG mode without using Ground Control Points (GCP). The preliminary results illustrate that horizontal DG positioning accuracies in the x and y axes are around 5 m with 300 m flight height. The positioning accuracy in the z axis is less than 10 m. Such accuracy is good for near real-time disaster relief. The DG ready function of proposed platform guarantees mapping and positioning capability even in GCP free environments, which is very important for rapid urgent response for disaster relief. Generally speaking, the data processing time for the DG module, including POS solution generalization, interpolation, Exterior Orientation Parameters (EOP) generation, and feature point measurements, is less than one hour.

Aerosol and Cloud Properties during the Cloud Cheju ABC Plume -Asian Monsoon Experiment (CAPMEX) 2008: Linking between Ground-based and UAV Measurements

NASA Astrophysics Data System (ADS)

Kim, S.; Yoon, S.; Venkata Ramana, M.; Ramanathan, V.; Nguyen, H.; Park, S.; Kim, M.

2009-12-01

Cheju Atmospheric Brown Cloud (ABC) Plume-Monsoon Experiment (CAPMEX), comprehsensive ground-based measurements and a series of data-gathering flights by specially equipped autonomous unmanned aerial vehicles (AUAVs) for aerosol and cloud, had conducted at Jeju (formerly, Cheju), South Korea during August-September 2008, to improve our understanding of how the reduction of anthropogenic emissions in China (so-called “great shutdown” ) during and after the Summer Beijing Olympic Games 2008 effcts on the air quliaty and radiation budgets and how atmospheric brown clouds (ABCs) influences solar radiation budget off Asian continent. Large numbers of in-situ and remote sensing instruments at the Gosan ABC observatory and miniaturized instruments on the aircraft measure a range of properties such as the quantity of soot, size-segregated aerosol particle numbers, total particle numbers, size-segregated cloud droplet numbers (only AUAV), aerosol scattering properties (only ground), aerosol vertical distribution, column-integrated aerosol properties, and meteorological variables. By integrating ground-level and high-elevation AUAV measurements with NASA-satellite observations (e.g., MODIS, CALIPSO), we investigate the long range transport of aerosols, the impact of ABCs on clouds, and the role of biogenic and anthropogenic aerosols on cloud condensation nuclei (CCN). In this talk, we will present the results from CAPMEX focusing on: (1) the characteristics of aerosol optical, physical and chemical properties at Gosan observatory, (2) aerosol solar heating calculated from the ground-based micro-pulse lidar and AERONET sun/sky radiometer synergy, and comparison with direct measurements from UAV, and (3) aerosol-cloud interactions in conjunction with measurements by satellites and Gosan observatory.

Autonomous mission management for UAVs using soar intelligent agents

NASA Astrophysics Data System (ADS)

Gunetti, Paolo; Thompson, Haydn; Dodd, Tony

2013-05-01

State-of-the-art unmanned aerial vehicles (UAVs) are typically able to autonomously execute a pre-planned mission. However, UAVs usually fly in a very dynamic environment which requires dynamic changes to the flight plan; this mission management activity is usually tasked to human supervision. Within this article, a software system that autonomously accomplishes the mission management task for a UAV will be proposed. The system is based on a set of theoretical concepts which allow the description of a flight plan and implemented using a combination of Soar intelligent agents and traditional control techniques. The system is capable of automatically generating and then executing an entire flight plan after being assigned a set of objectives. This article thoroughly describes all system components and then presents the results of tests that were executed using a realistic simulation environment.

Methane Leak Detection and Emissions Quantification with UAVs

NASA Astrophysics Data System (ADS)

Barchyn, T.; Fox, T. A.; Hugenholtz, C.

2016-12-01

Robust leak detection and emissions quantification algorithms are required to accurately monitor greenhouse gas emissions. Unmanned aerial vehicles (UAVs, `drones') could both reduce the cost and increase the accuracy of monitoring programs. However, aspects of the platform create unique challenges. UAVs typically collect large volumes of data that are close to source (due to limited range) and often lower quality (due to weight restrictions on sensors). Here we discuss algorithm development for (i) finding sources of unknown position (`leak detection') and (ii) quantifying emissions from a source of known position. We use data from a simulated leak and field study in Alberta, Canada. First, we detail a method for localizing a leak of unknown spatial location using iterative fits against a forward Gaussian plume model. We explore sources of uncertainty, both inherent to the method and operational. Results suggest this method is primarily constrained by accurate wind direction data, distance downwind from source, and the non-Gaussian shape of close range plumes. Second, we examine sources of uncertainty in quantifying emissions with the mass balance method. Results suggest precision is constrained by flux plane interpolation errors and time offsets between spatially adjacent measurements. Drones can provide data closer to the ground than piloted aircraft, but large portions of the plume are still unquantified. Together, we find that despite larger volumes of data, working with close range plumes as measured with UAVs is inherently difficult. We describe future efforts to mitigate these challenges and work towards more robust benchmarking for application in industrial and regulatory settings.

Rapid melting dynamics of an alpine glacier with repeated UAV photogrammetry

NASA Astrophysics Data System (ADS)

Rossini, Micol; Di Mauro, Biagio; Garzonio, Roberto; Baccolo, Giovanni; Cavallini, Giuseppe; Mattavelli, Matteo; De Amicis, Mattia; Colombo, Roberto

2018-03-01

Glacial retreat is a major problem in the Alps, especially over the past 40 years. Unmanned aerial vehicles (UAVs) can provide an unparalleled opportunity to track the spatiotemporal variations in rapidly changing glacial morphological features related to glacial dynamics. The objective of this study is to evaluate the potential of commercial UAV platforms to detect the evolution of the surface topography and morphology of an alpine glacier over a short time scale through the repeated acquisition of high-resolution photogrammetric data. Two high-resolution UAV surveys were performed on the ablation region of the Morteratsch Glacier (Swiss Alps) in July and September 2016. First, structure-from-motion (SfM) techniques were applied to create orthophotos and digital surface models (DSMs) of the glacial surface from multi-view UAV acquisitions. The geometric accuracy of DSMs and orthophotos was checked using differential global navigation satellite system (dGNSS) ground measurements, and an accuracy of approximately 17 cm was achieved for both models. High-resolution orthophotos and DSMs made it possible to provide a detailed characterization of rapidly changing glacial environments. Comparing the data from the first and the second campaigns, the evolution of the lower part of the glacier in response to summer ablation was evaluated. Two distinct processes were revealed and accurately quantified: an average lowering of the surface, with a mean ice thinning of 4 m, and an average horizontal displacement of 3 m due to flowing ice. These data were validated through a comparison of different algorithms and approaches, which clearly showed the consistency of the results. The melt rate spatial patterns were then compared to the glacial brightness and roughness maps derived from the September UAV acquisition. The results showed that the DSM differences describing the glacial melt rates were inversely related to the glacial brightness. In contrast, a positive but weaker relationship existed between the DSM differences and glacial roughness. This research demonstrates that UAV photogrammetry allows the qualitative and quantitative appreciation of the complex evolution of retreating glaciers at a centimetre scale spatial resolution. Such performance allows the detection of seasonal changes in the surface topography, which are related to summer ablation and span from the processes affecting the entire glacier to those that are more local.

Evaluation of the Quality of Action Cameras with Wide-Angle Lenses in Uav Photogrammetry

NASA Astrophysics Data System (ADS)

Hastedt, H.; Ekkel, T.; Luhmann, T.

2016-06-01

The application of light-weight cameras in UAV photogrammetry is required due to restrictions in payload. In general, consumer cameras with normal lens type are applied to a UAV system. The availability of action cameras, like the GoPro Hero4 Black, including a wide-angle lens (fish-eye lens) offers new perspectives in UAV projects. With these investigations, different calibration procedures for fish-eye lenses are evaluated in order to quantify their accuracy potential in UAV photogrammetry. Herewith the GoPro Hero4 is evaluated using different acquisition modes. It is investigated to which extent the standard calibration approaches in OpenCV or Agisoft PhotoScan/Lens can be applied to the evaluation processes in UAV photogrammetry. Therefore different calibration setups and processing procedures are assessed and discussed. Additionally a pre-correction of the initial distortion by GoPro Studio and its application to the photogrammetric purposes will be evaluated. An experimental setup with a set of control points and a prospective flight scenario is chosen to evaluate the processing results using Agisoft PhotoScan. Herewith it is analysed to which extent a pre-calibration and pre-correction of a GoPro Hero4 will reinforce the reliability and accuracy of a flight scenario.

UAV-Based Estimation of Carbon Exports from Heterogeneous Soil Landscapes—A Case Study from the CarboZALF Experimental Area

PubMed Central

Wehrhan, Marc; Rauneker, Philipp; Sommer, Michael

2016-01-01

The advantages of remote sensing using Unmanned Aerial Vehicles (UAVs) are a high spatial resolution of images, temporal flexibility and narrow-band spectral data from different wavelengths domains. This enables the detection of spatio-temporal dynamics of environmental variables, like plant-related carbon dynamics in agricultural landscapes. In this paper, we quantify spatial patterns of fresh phytomass and related carbon (C) export using imagery captured by a 12-band multispectral camera mounted on the fixed wing UAV Carolo P360. The study was performed in 2014 at the experimental area CarboZALF-D in NE Germany. From radiometrically corrected and calibrated images of lucerne (Medicago sativa), the performance of four commonly used vegetation indices (VIs) was tested using band combinations of six near-infrared bands. The highest correlation between ground-based measurements of fresh phytomass of lucerne and VIs was obtained for the Enhanced Vegetation Index (EVI) using near-infrared band b899. The resulting map was transformed into dry phytomass and finally upscaled to total C export by harvest. The observed spatial variability at field- and plot-scale could be attributed to small-scale soil heterogeneity in part. PMID:26907284

UAV-Based Estimation of Carbon Exports from Heterogeneous Soil Landscapes--A Case Study from the CarboZALF Experimental Area.

PubMed

Wehrhan, Marc; Rauneker, Philipp; Sommer, Michael

2016-02-19

The advantages of remote sensing using Unmanned Aerial Vehicles (UAVs) are a high spatial resolution of images, temporal flexibility and narrow-band spectral data from different wavelengths domains. This enables the detection of spatio-temporal dynamics of environmental variables, like plant-related carbon dynamics in agricultural landscapes. In this paper, we quantify spatial patterns of fresh phytomass and related carbon (C) export using imagery captured by a 12-band multispectral camera mounted on the fixed wing UAV Carolo P360. The study was performed in 2014 at the experimental area CarboZALF-D in NE Germany. From radiometrically corrected and calibrated images of lucerne (Medicago sativa), the performance of four commonly used vegetation indices (VIs) was tested using band combinations of six near-infrared bands. The highest correlation between ground-based measurements of fresh phytomass of lucerne and VIs was obtained for the Enhanced Vegetation Index (EVI) using near-infrared band b899. The resulting map was transformed into dry phytomass and finally upscaled to total C export by harvest. The observed spatial variability at field- and plot-scale could be attributed to small-scale soil heterogeneity in part.

Design and implementation of a remote UAV-based mobile health monitoring system

NASA Astrophysics Data System (ADS)

Li, Songwei; Wan, Yan; Fu, Shengli; Liu, Mushuang; Wu, H. Felix

2017-04-01

Unmanned aerial vehicles (UAVs) play increasing roles in structure health monitoring. With growing mobility in modern Internet-of-Things (IoT) applications, the health monitoring of mobile structures becomes an emerging application. In this paper, we develop a UAV-carried vision-based monitoring system that allows a UAV to continuously track and monitor a mobile infrastructure and transmit back the monitoring information in real- time from a remote location. The monitoring system uses a simple UAV-mounted camera and requires only a single feature located on the mobile infrastructure for target detection and tracking. The computation-effective vision-based tracking solution based on a single feature is an improvement over existing vision-based lead-follower tracking systems that either have poor tracking performance due to the use of a single feature, or have improved tracking performance at a cost of the usage of multiple features. In addition, a UAV-carried aerial networking infrastructure using directional antennas is used to enable robust real-time transmission of monitoring video streams over a long distance. Automatic heading control is used to self-align headings of directional antennas to enable robust communication in mobility. Compared to existing omni-communication systems, the directional communication solution significantly increases the operation range of remote monitoring systems. In this paper, we develop the integrated modeling framework of camera and mobile platforms, design the tracking algorithm, develop a testbed of UAVs and mobile platforms, and evaluate system performance through both simulation studies and field tests.

An automated 3D reconstruction method of UAV images

NASA Astrophysics Data System (ADS)

Liu, Jun; Wang, He; Liu, Xiaoyang; Li, Feng; Sun, Guangtong; Song, Ping

2015-10-01

In this paper a novel fully automated 3D reconstruction approach based on low-altitude unmanned aerial vehicle system (UAVs) images will be presented, which does not require previous camera calibration or any other external prior knowledge. Dense 3D point clouds are generated by integrating orderly feature extraction, image matching, structure from motion (SfM) and multi-view stereo (MVS) algorithms, overcoming many of the cost, time limitations of rigorous photogrammetry techniques. An image topology analysis strategy is introduced to speed up large scene reconstruction by taking advantage of the flight-control data acquired by UAV. Image topology map can significantly reduce the running time of feature matching by limiting the combination of images. A high-resolution digital surface model of the study area is produced base on UAV point clouds by constructing the triangular irregular network. Experimental results show that the proposed approach is robust and feasible for automatic 3D reconstruction of low-altitude UAV images, and has great potential for the acquisition of spatial information at large scales mapping, especially suitable for rapid response and precise modelling in disaster emergency.